move_webui #35
@@ -1,8 +1,6 @@
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name: Code Quality Pipeline
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run-name: ${{ gitea.actor }} is running the Code Quality Pipeline
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runs-on: ubuntu-latest
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on: push
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image: python:3.12
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jobs:
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test:
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name: Test
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@@ -21,7 +19,7 @@ jobs:
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poetry install
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- name: PEP8 Check
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run: |
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poetry run flake8 ./src --benchmark
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poetry run flake8 . --benchmark
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- name: Type Check
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run: |
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poetry run mypy ./src --disable-error-code=import-untyped
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poetry run mypy . --disable-error-code=import-untyped
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@@ -1,6 +1,5 @@
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name: CI Pipeline
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run-name: ${{ gitea.actor }} is running the CI Pipeline
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runs-on: ubuntu-latest
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on:
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pull_request:
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branches:
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@@ -23,30 +22,52 @@ jobs:
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poetry install
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- name: PEP8 Check
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run: |
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poetry run flake8 ./src --benchmark
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poetry run flake8 . --benchmark
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- name: Type Check
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run: |
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poetry run mypy ./src --disable-error-code=import-untyped
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poetry run mypy . --disable-error-code=import-untyped
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publish:
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name: Build and Publish
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runs-on: ubuntu-latest
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needs: [test]
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strategy:
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fail-fast: false
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matrix:
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include:
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-
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dockerfile: ./Dockerfile.web_ui
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image: ${{ vars.docker_repo_url }}/${{ gitea.repository }}/web_ui
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# -
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# dockerfile: ./model/Dockerfile
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# image: ${{ vars.docker_repo_url }}/${{ gitea.repository }}/model
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steps:
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- name: Checkout Code
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-
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name: Checkout Code
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uses: actions/checkout@v3
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- name: Set Environment Variables
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-
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name: Set Environment Variables
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run: |
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echo "sha_short=$(git rev-parse --short ${{ gitea.sha }} )" >> "$GITHUB_ENV"
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- name: Show Environment Variables
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-
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name: Show Environment Variables
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run: |
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echo "DOCKER_REPO_URL: ${{ vars.docker_repo_url }}"
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echo "REPOSITORY: ${{ gitea.repository }}"
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echo "COMMIT_SHA: ${{ env.sha_short }}"
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- name: Build and Push Image
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uses: docker/build-push-action@v2
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-
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name: Extract metadata (tags, labels) for Docker
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id: meta
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uses: docker/metadata-action@v5
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with:
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images: ${{ matrix.image }}
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-
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name: Build and Push Image
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uses: docker/build-push-action@v4
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with:
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context: .
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file: ${{ matrix.dockerfile }}
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push: true
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tags: |
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${{ vars.docker_repo_url }}/${{ gitea.repository }}:${{ env.sha_short }}
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${{ vars.docker_repo_url }}/${{ gitea.repository }}:latest
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${{ matrix.image }}:${{ env.sha_short }}
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${{ matrix.image }}:latest
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labels: ${{ steps.meta.outputs.labels }}
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@@ -0,0 +1,58 @@
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# build stage
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FROM python:3.12-slim-bookworm as BUILDER
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# set environment variables
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ENV PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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PIP_NO_CACHE_DIR=off \
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PIP_DISABLE_PIP_VERSION_CHECK=ON \
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PIP_DEFAULT_TIMEOUT=100 \
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DEBIAN_FRONTEND=noninteractive \
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POETRY_HOME=/etc/poetry \
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POETRY_VERSION=1.7.1 \
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POETRY_VIRTUALENVS_IN_PROJECT=1 \
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POETRY_VIRTUALENVS_CREATE=1 \
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POETRY_NO_INTERACTION=1 \
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POETRY_CACHE_DIR=/tmp/poetry_cache \
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APP_HOME=/home/app
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# update system
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RUN apt-get update \
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&& apt-get install -y --no-install-recommends \
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build-essential \
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curl \
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&& apt-get clean
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# install poetry
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RUN curl -sSL https://install.python-poetry.org | python3 -
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ENV PATH="${POETRY_HOME}/bin:$PATH"
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# install runtime dependencies
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WORKDIR ${APP_HOME}
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COPY ./poetry.lock ./pyproject.toml ./
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RUN --mount=type=cache,target=${POETRY_CACHE_DIR} poetry install \
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--with shared,web_ui
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# final stage
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FROM python:3.12-slim-bookworm
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# copy virtualenv made by poetry
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ENV APP_HOME=/home/app \
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VIRTUAL_ENV=/home/app/.venv
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COPY --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
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ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"
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# create home directory and app user
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RUN mkdir -p /home/app && \
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addgroup --system app && \
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adduser --system --group app
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# add code while changing ownership
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WORKDIR $APP_HOME
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COPY --chown=app:app ./shared ./shared
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COPY --chown=app:app ./web_ui/src ./src
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# change to the app user
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USER app
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ENTRYPOINT [ "gunicorn", "src.main:server", "-b", "0.0.0.0:8050" ]
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+16
-17
@@ -1,21 +1,20 @@
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version: '3.7'
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services:
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# app:
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# image: visual_critical_discourse_analysis:dev
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# container_name: visual_critical_discourse_analysis
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# build:
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# context: .
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# dockerfile: Dockerfile
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# env_file:
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# - local.env
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# environment:
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# - ENV=DEV
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# ports:
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# - 8050:8050
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# networks:
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# - backend
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# depends_on:
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# - mongo
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app:
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image: visual_critical_discourse_analysis:dev
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container_name: visual_critical_discourse_analysis
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build:
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context: .
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dockerfile: ./web_ui/Dockerfile
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env_file:
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- local.env
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environment:
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- ENV=DEV
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ports:
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- 8050:8050
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networks:
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- backend
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depends_on:
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- mongo
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mongo:
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image: mongo:latest
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container_name: mongo
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@@ -1,11 +1,10 @@
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version: '3.7'
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services:
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app:
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image: visual_critical_discourse_analysis:dev
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container_name: visual_critical_discourse_analysis
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build:
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context: .
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dockerfile: Dockerfile
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dockerfile: ./web_ui/Dockerfile
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env_file:
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- server.env
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ports:
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@@ -6,10 +6,9 @@ from pathlib import Path
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import pandas as pd
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import requests
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from classes import Instagram
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from retry import retry
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from image_download.classes import Instagram
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def get_sources() -> pd.DataFrame:
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"""Get sources dateframe."""
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@@ -14,7 +14,7 @@ from torchvision.transforms.functional import pad
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from torchvision.transforms.functional import resize
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from torchvision.transforms.functional import rotate
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from core.database import connect
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from shared.database import connect
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# resnet18 original normalization values
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RESNET_NORMALIZE_MEAN = [0.485, 0.456, 0.406]
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@@ -14,17 +14,17 @@ from .point_of_view import PointOfViewTail
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from .resnet18_head import ResNet18Head
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from .salience import SalienceTail
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from .visual_syntax import VisualSyntaxTail
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from core.dto import AngleData
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from core.dto import ContactData
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from core.dto import DistanceData
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from core.dto import FramingData
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from core.dto import InformationValueData
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from core.dto import ModalityColorData
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from core.dto import ModalityDepthData
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from core.dto import ModalityLightingData
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from core.dto import PointOfViewData
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from core.dto import SalienceData
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from core.dto import VisualSyntaxData
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from shared.dto import AngleData
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from shared.dto import ContactData
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from shared.dto import DistanceData
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from shared.dto import FramingData
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from shared.dto import InformationValueData
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from shared.dto import ModalityColorData
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from shared.dto import ModalityDepthData
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from shared.dto import ModalityLightingData
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from shared.dto import PointOfViewData
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from shared.dto import SalienceData
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from shared.dto import VisualSyntaxData
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class VisualCommunicationModel(nn.Module):
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Generated
+108
-104
@@ -32,13 +32,13 @@ tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "p
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[[package]]
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name = "blinker"
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version = "1.8.1"
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version = "1.8.2"
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description = "Fast, simple object-to-object and broadcast signaling"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "blinker-1.8.1-py3-none-any.whl", hash = "sha256:5f1cdeff423b77c31b89de0565cd03e5275a03028f44b2b15f912632a58cced6"},
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{file = "blinker-1.8.1.tar.gz", hash = "sha256:da44ec748222dcd0105ef975eed946da197d5bdf8bafb6aa92f5bc89da63fa25"},
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{file = "blinker-1.8.2-py3-none-any.whl", hash = "sha256:1779309f71bf239144b9399d06ae925637cf6634cf6bd131104184531bf67c01"},
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{file = "blinker-1.8.2.tar.gz", hash = "sha256:8f77b09d3bf7c795e969e9486f39c2c5e9c39d4ee07424be2bc594ece9642d83"},
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]
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[[package]]
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@@ -242,13 +242,13 @@ files = [
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[[package]]
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name = "dash"
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version = "2.16.1"
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version = "2.17.0"
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description = "A Python framework for building reactive web-apps. Developed by Plotly."
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "dash-2.16.1-py3-none-any.whl", hash = "sha256:8a9d2a618e415113c0b2a4d25d5dc4df5cb921f733b33dde75559db2316b1df1"},
|
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{file = "dash-2.16.1.tar.gz", hash = "sha256:b2871d6b8d4c9dfd0a64f89f22d001c93292910b41d92d9ff2bb424a28283976"},
|
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{file = "dash-2.17.0-py3-none-any.whl", hash = "sha256:2421569023b2cd46ea2d4b2c14fe72c71b7436527a3102219b2265fa361e7c67"},
|
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{file = "dash-2.17.0.tar.gz", hash = "sha256:d065cd88771e45d0485993be0d27565e08918cb7edd18e31ee1c5b41252fc2fa"},
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]
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[package.dependencies]
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@@ -267,7 +267,7 @@ Werkzeug = "<3.1"
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[package.extras]
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celery = ["celery[redis] (>=5.1.2)", "redis (>=3.5.3)"]
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ci = ["black (==22.3.0)", "dash-dangerously-set-inner-html", "dash-flow-example (==0.0.5)", "flake8 (==7.0.0)", "flaky (==3.7.0)", "flask-talisman (==1.0.0)", "jupyterlab (<4.0.0)", "mimesis (<=11.1.0)", "mock (==4.0.3)", "numpy (<=1.26.3)", "openpyxl", "orjson (==3.9.12)", "pandas (>=1.4.0)", "pyarrow", "pylint (==3.0.3)", "pytest-mock", "pytest-rerunfailures", "pytest-sugar (==0.9.6)", "pyzmq (==25.1.2)", "xlrd (>=2.0.1)"]
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ci = ["black (==22.3.0)", "dash-dangerously-set-inner-html", "dash-flow-example (==0.0.5)", "flake8 (==7.0.0)", "flaky (==3.8.1)", "flask-talisman (==1.0.0)", "jupyterlab (<4.0.0)", "mimesis (<=11.1.0)", "mock (==4.0.3)", "numpy (<=1.26.3)", "openpyxl", "orjson (==3.9.12)", "pandas (>=1.4.0)", "pyarrow", "pylint (==3.0.3)", "pytest-mock", "pytest-rerunfailures", "pytest-sugar (==0.9.6)", "pyzmq (==25.1.2)", "xlrd (>=2.0.1)"]
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compress = ["flask-compress"]
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dev = ["PyYAML (>=5.4.1)", "coloredlogs (>=15.0.1)", "fire (>=0.4.0)"]
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diskcache = ["diskcache (>=5.2.1)", "multiprocess (>=0.70.12)", "psutil (>=5.8.0)"]
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@@ -440,13 +440,13 @@ dotenv = ["python-dotenv"]
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[[package]]
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name = "fsspec"
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version = "2024.3.1"
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version = "2024.5.0"
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description = "File-system specification"
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optional = false
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python-versions = ">=3.8"
|
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files = [
|
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{file = "fsspec-2024.3.1-py3-none-any.whl", hash = "sha256:918d18d41bf73f0e2b261824baeb1b124bcf771767e3a26425cd7dec3332f512"},
|
||||
{file = "fsspec-2024.3.1.tar.gz", hash = "sha256:f39780e282d7d117ffb42bb96992f8a90795e4d0fb0f661a70ca39fe9c43ded9"},
|
||||
{file = "fsspec-2024.5.0-py3-none-any.whl", hash = "sha256:e0fdbc446d67e182f49a70b82cf7889028a63588fde6b222521f10937b2b670c"},
|
||||
{file = "fsspec-2024.5.0.tar.gz", hash = "sha256:1d021b0b0f933e3b3029ed808eb400c08ba101ca2de4b3483fbc9ca23fcee94a"},
|
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]
|
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|
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[package.extras]
|
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@@ -454,7 +454,7 @@ abfs = ["adlfs"]
|
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adl = ["adlfs"]
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arrow = ["pyarrow (>=1)"]
|
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dask = ["dask", "distributed"]
|
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devel = ["pytest", "pytest-cov"]
|
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dev = ["pre-commit", "ruff"]
|
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dropbox = ["dropbox", "dropboxdrivefs", "requests"]
|
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full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
|
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fuse = ["fusepy"]
|
||||
@@ -471,6 +471,9 @@ s3 = ["s3fs"]
|
||||
sftp = ["paramiko"]
|
||||
smb = ["smbprotocol"]
|
||||
ssh = ["paramiko"]
|
||||
test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
|
||||
test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
|
||||
test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
|
||||
tqdm = ["tqdm"]
|
||||
|
||||
[[package]]
|
||||
@@ -547,13 +550,13 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "jinja2"
|
||||
version = "3.1.3"
|
||||
version = "3.1.4"
|
||||
description = "A very fast and expressive template engine."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "Jinja2-3.1.3-py3-none-any.whl", hash = "sha256:7d6d50dd97d52cbc355597bd845fabfbac3f551e1f99619e39a35ce8c370b5fa"},
|
||||
{file = "Jinja2-3.1.3.tar.gz", hash = "sha256:ac8bd6544d4bb2c9792bf3a159e80bba8fda7f07e81bc3aed565432d5925ba90"},
|
||||
{file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
|
||||
{file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -1113,13 +1116,13 @@ xmp = ["defusedxml"]
|
||||
|
||||
[[package]]
|
||||
name = "plotly"
|
||||
version = "5.21.0"
|
||||
version = "5.22.0"
|
||||
description = "An open-source, interactive data visualization library for Python"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "plotly-5.21.0-py3-none-any.whl", hash = "sha256:a33f41fd5922e45b2b253f795b200d14452eb625790bb72d0a72cf1328a6abbf"},
|
||||
{file = "plotly-5.21.0.tar.gz", hash = "sha256:69243f8c165d4be26c0df1c6f0b7b258e2dfeefe032763404ad7e7fb7d7c2073"},
|
||||
{file = "plotly-5.22.0-py3-none-any.whl", hash = "sha256:68fc1901f098daeb233cc3dd44ec9dc31fb3ca4f4e53189344199c43496ed006"},
|
||||
{file = "plotly-5.22.0.tar.gz", hash = "sha256:859fdadbd86b5770ae2466e542b761b247d1c6b49daed765b95bb8c7063e7469"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -1282,71 +1285,71 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "pymongo"
|
||||
version = "4.7.1"
|
||||
version = "4.7.2"
|
||||
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{file = "pymongo-4.7.2-cp38-cp38-win_amd64.whl", hash = "sha256:4bdb5ffe1cd3728c9479671a067ef44dacafc3743741d4dc700c377c4231356f"},
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||||
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||||
{file = "pymongo-4.7.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5239776633f7578b81207e5646245415a5a95f6ae5ef5dff8e7c2357e6264bfc"},
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{file = "pymongo-4.7.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:727ad07952c155cd20045f2ce91143c7dc4fb01a5b4e8012905a89a7da554b0c"},
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{file = "pymongo-4.7.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9385654f01a90f73827af4db90c290a1519f7d9102ba43286e187b373e9a78e9"},
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||||
{file = "pymongo-4.7.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0d833651f1ba938bb7501f13e326b96cfbb7d98867b2d545ca6d69c7664903e0"},
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||||
{file = "pymongo-4.7.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cf17ea9cea14d59b0527403dd7106362917ced7c4ec936c4ba22bd36c912c8e0"},
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||||
{file = "pymongo-4.7.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:cecd2df037249d1c74f0af86fb5b766104a5012becac6ff63d85d1de53ba8b98"},
|
||||
{file = "pymongo-4.7.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:65b4c00dedbd333698b83cd2095a639a6f0d7c4e2a617988f6c65fb46711f028"},
|
||||
{file = "pymongo-4.7.2-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:d9b6cbc037108ff1a0a867e7670d8513c37f9bcd9ee3d2464411bfabf70ca002"},
|
||||
{file = "pymongo-4.7.2-cp39-cp39-win32.whl", hash = "sha256:cf28430ec1924af1bffed37b69a812339084697fd3f3e781074a0148e6475803"},
|
||||
{file = "pymongo-4.7.2-cp39-cp39-win_amd64.whl", hash = "sha256:e004527ea42a6b99a8b8d5b42b42762c3bdf80f88fbdb5c3a9d47f3808495b86"},
|
||||
{file = "pymongo-4.7.2.tar.gz", hash = "sha256:9024e1661c6e40acf468177bf90ce924d1bc681d2b244adda3ed7b2f4c4d17d7"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -1414,13 +1417,13 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.31.0"
|
||||
version = "2.32.0"
|
||||
description = "Python HTTP for Humans."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
|
||||
{file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
|
||||
{file = "requests-2.32.0-py3-none-any.whl", hash = "sha256:f2c3881dddb70d056c5bd7600a4fae312b2a300e39be6a118d30b90bd27262b5"},
|
||||
{file = "requests-2.32.0.tar.gz", hash = "sha256:fa5490319474c82ef1d2c9bc459d3652e3ae4ef4c4ebdd18a21145a47ca4b6b8"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -1464,13 +1467,13 @@ six = ">=1.7.0"
|
||||
|
||||
[[package]]
|
||||
name = "selenium"
|
||||
version = "4.20.0"
|
||||
version = "4.21.0"
|
||||
description = ""
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "selenium-4.20.0-py3-none-any.whl", hash = "sha256:b1d0c33b38ca27d0499183e48e1dd09ff26973481f5d3ef2983073813ae6588d"},
|
||||
{file = "selenium-4.20.0.tar.gz", hash = "sha256:0bd564ee166980d419a8aaf4ac00289bc152afcf2eadca5efe8c8e36711853fd"},
|
||||
{file = "selenium-4.21.0-py3-none-any.whl", hash = "sha256:4770ffe5a5264e609de7dc914be6b89987512040d5a8efb2abb181330d097993"},
|
||||
{file = "selenium-4.21.0.tar.gz", hash = "sha256:650dbfa5159895ff00ad16e5ddb6ceecb86b90c7ed2012b3f041f64e6e4904fe"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -1545,17 +1548,18 @@ mpmath = ">=0.19"
|
||||
|
||||
[[package]]
|
||||
name = "tenacity"
|
||||
version = "8.2.3"
|
||||
version = "8.3.0"
|
||||
description = "Retry code until it succeeds"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "tenacity-8.2.3-py3-none-any.whl", hash = "sha256:ce510e327a630c9e1beaf17d42e6ffacc88185044ad85cf74c0a8887c6a0f88c"},
|
||||
{file = "tenacity-8.2.3.tar.gz", hash = "sha256:5398ef0d78e63f40007c1fb4c0bff96e1911394d2fa8d194f77619c05ff6cc8a"},
|
||||
{file = "tenacity-8.3.0-py3-none-any.whl", hash = "sha256:3649f6443dbc0d9b01b9d8020a9c4ec7a1ff5f6f3c6c8a036ef371f573fe9185"},
|
||||
{file = "tenacity-8.3.0.tar.gz", hash = "sha256:953d4e6ad24357bceffbc9707bc74349aca9d245f68eb65419cf0c249a1949a2"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
doc = ["reno", "sphinx", "tornado (>=4.5)"]
|
||||
doc = ["reno", "sphinx"]
|
||||
test = ["pytest", "tornado (>=4.5)", "typeguard"]
|
||||
|
||||
[[package]]
|
||||
name = "torch"
|
||||
@@ -1658,13 +1662,13 @@ scipy = ["scipy"]
|
||||
|
||||
[[package]]
|
||||
name = "trio"
|
||||
version = "0.25.0"
|
||||
version = "0.25.1"
|
||||
description = "A friendly Python library for async concurrency and I/O"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "trio-0.25.0-py3-none-any.whl", hash = "sha256:e6458efe29cc543e557a91e614e2b51710eba2961669329ce9c862d50c6e8e81"},
|
||||
{file = "trio-0.25.0.tar.gz", hash = "sha256:9b41f5993ad2c0e5f62d0acca320ec657fdb6b2a2c22b8c7aed6caf154475c4e"},
|
||||
{file = "trio-0.25.1-py3-none-any.whl", hash = "sha256:e42617ba091e7b2e50c899052e83a3c403101841de925187f61e7b7eaebdf3fb"},
|
||||
{file = "trio-0.25.1.tar.gz", hash = "sha256:9f5314f014ea3af489e77b001861c535005c3858d38ec46b6b071ebfa339d7fb"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -1692,13 +1696,13 @@ wsproto = ">=0.14"
|
||||
|
||||
[[package]]
|
||||
name = "types-pillow"
|
||||
version = "10.2.0.20240423"
|
||||
version = "10.2.0.20240520"
|
||||
description = "Typing stubs for Pillow"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "types-Pillow-10.2.0.20240423.tar.gz", hash = "sha256:696e68b9b6a58548fc307a8669830469237c5b11809ddf978ac77fafa79251cd"},
|
||||
{file = "types_Pillow-10.2.0.20240423-py3-none-any.whl", hash = "sha256:bd12923093b96c91d523efcdb66967a307f1a843bcfaf2d5a529146c10a9ced3"},
|
||||
{file = "types-Pillow-10.2.0.20240520.tar.gz", hash = "sha256:130b979195465fa1e1676d8e81c9c7c30319e8e95b12fae945e8f0d525213107"},
|
||||
{file = "types_Pillow-10.2.0.20240520-py3-none-any.whl", hash = "sha256:33c36494b380e2a269bb742181bea5d9b00820367822dbd3760f07210a1da23d"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -1761,13 +1765,13 @@ requests = "*"
|
||||
|
||||
[[package]]
|
||||
name = "werkzeug"
|
||||
version = "3.0.2"
|
||||
version = "3.0.3"
|
||||
description = "The comprehensive WSGI web application library."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "werkzeug-3.0.2-py3-none-any.whl", hash = "sha256:3aac3f5da756f93030740bc235d3e09449efcf65f2f55e3602e1d851b8f48795"},
|
||||
{file = "werkzeug-3.0.2.tar.gz", hash = "sha256:e39b645a6ac92822588e7b39a692e7828724ceae0b0d702ef96701f90e70128d"},
|
||||
{file = "werkzeug-3.0.3-py3-none-any.whl", hash = "sha256:fc9645dc43e03e4d630d23143a04a7f947a9a3b5727cd535fdfe155a17cc48c8"},
|
||||
{file = "werkzeug-3.0.3.tar.gz", hash = "sha256:097e5bfda9f0aba8da6b8545146def481d06aa7d3266e7448e2cccf67dd8bd18"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -1792,20 +1796,20 @@ h11 = ">=0.9.0,<1"
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.18.1"
|
||||
version = "3.18.2"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zipp-3.18.1-py3-none-any.whl", hash = "sha256:206f5a15f2af3dbaee80769fb7dc6f249695e940acca08dfb2a4769fe61e538b"},
|
||||
{file = "zipp-3.18.1.tar.gz", hash = "sha256:2884ed22e7d8961de1c9a05142eb69a247f120291bc0206a00a7642f09b5b715"},
|
||||
{file = "zipp-3.18.2-py3-none-any.whl", hash = "sha256:dce197b859eb796242b0622af1b8beb0a722d52aa2f57133ead08edd5bf5374e"},
|
||||
{file = "zipp-3.18.2.tar.gz", hash = "sha256:6278d9ddbcfb1f1089a88fde84481528b07b0e10474e09dcfe53dad4069fa059"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
|
||||
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.12"
|
||||
content-hash = "6c4bb66c774e93a08e4180f3148942edf91e2b5620ea1f6c3e4c30045bb643e5"
|
||||
content-hash = "2db221a28d46b210a8fa0b78ad2fa3ac606a52052ad5e02b50d5b07db1e1c5b7"
|
||||
|
||||
+15
-10
@@ -5,20 +5,11 @@ description = ""
|
||||
authors = ["Brian Bjarke Jensen <[email protected]>"]
|
||||
readme = "README.md"
|
||||
packages = [
|
||||
{ include = "core" },
|
||||
{ include = "shared" },
|
||||
]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.12"
|
||||
gunicorn = "^21.2.0"
|
||||
python-dotenv = "^1.0.1"
|
||||
dash = "^2.15.0"
|
||||
dash-bootstrap-components = "^1.5.0"
|
||||
dash-mantine-components = "^0.12.1"
|
||||
pydantic = "^2.6.1"
|
||||
pillow = "^10.2.0"
|
||||
pymongo = "^4.6.1"
|
||||
dash-auth = "^2.2.0"
|
||||
|
||||
|
||||
[tool.poetry.group.test.dependencies]
|
||||
@@ -38,6 +29,20 @@ retry = "^0.9.2"
|
||||
torch = "^2.2.1"
|
||||
torchvision = "^0.17.1"
|
||||
|
||||
|
||||
[tool.poetry.group.shared.dependencies]
|
||||
pymongo = "^4.7.2"
|
||||
pydantic = "^2.6.1"
|
||||
pillow = "^10.2.0"
|
||||
|
||||
|
||||
[tool.poetry.group.web_ui.dependencies]
|
||||
dash = "^2.17.0"
|
||||
gunicorn = "^21.2.0"
|
||||
dash-bootstrap-components = "^1.5.0"
|
||||
dash-mantine-components = "^0.12.1"
|
||||
dash-auth = "^2.2.0"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
+1
-1
@@ -12,7 +12,7 @@ from pydantic import BaseModel
|
||||
from pydantic import field_serializer
|
||||
from pydantic import field_validator
|
||||
|
||||
from core.dto import ModelData
|
||||
from shared.dto import ModelData
|
||||
|
||||
|
||||
class VisualCommunication(BaseModel):
|
||||
+2
-2
@@ -5,8 +5,8 @@ import logging
|
||||
|
||||
from pymongo.collection import Collection
|
||||
|
||||
from core.database import NoDocumentFoundException
|
||||
from core.database import VisualCommunication
|
||||
from shared.database import NoDocumentFoundException
|
||||
from shared.database import VisualCommunication
|
||||
|
||||
|
||||
def get_visual_communication(
|
||||
@@ -4,7 +4,7 @@ import logging
|
||||
|
||||
from pymongo.collection import Collection
|
||||
|
||||
from core.database import Dataset
|
||||
from shared.database import Dataset
|
||||
|
||||
|
||||
def save_dataset(
|
||||
@@ -21,7 +21,7 @@ def save_dataset(
|
||||
if __name__ == '__main__':
|
||||
from dotenv import load_dotenv
|
||||
load_dotenv('local.env')
|
||||
from core.database import list_names, connect
|
||||
from shared.database import list_names, connect
|
||||
# connect to database
|
||||
collection, db, client = connect()
|
||||
print(client.server_info())
|
||||
+1
-1
@@ -4,7 +4,7 @@ import logging
|
||||
|
||||
from pymongo.collection import Collection
|
||||
|
||||
from core.dto import ModelData
|
||||
from shared.dto import ModelData
|
||||
|
||||
|
||||
def upsert_annotation(
|
||||
+1
-1
@@ -4,7 +4,7 @@ import logging
|
||||
|
||||
from pymongo.collection import Collection
|
||||
|
||||
from core.dto import ModelData
|
||||
from shared.dto import ModelData
|
||||
|
||||
|
||||
def upsert_prediction(
|
||||
+1
-1
@@ -2,7 +2,7 @@ from __future__ import annotations
|
||||
|
||||
from pymongo.collection import Collection
|
||||
|
||||
from core.database import VisualCommunication
|
||||
from shared.database import VisualCommunication
|
||||
|
||||
|
||||
def upsert_visual_communication(
|
||||
@@ -0,0 +1,4 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from .check_env import check_env
|
||||
from .setup_logging import setup_logging
|
||||
@@ -0,0 +1,24 @@
|
||||
"""Definition of check_env function."""
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
|
||||
|
||||
def check_env() -> None:
|
||||
"""Check necessary environment variables are set."""
|
||||
necesasary_var_list = {
|
||||
'MONGO_HOST',
|
||||
'MONGO_DB',
|
||||
'MONGO_COLLECTION',
|
||||
'MONGO_USER',
|
||||
'MONGO_PASSWORD',
|
||||
'DASH_AUTH_USERNAME',
|
||||
'DASH_AUTH_PASSWORD',
|
||||
}
|
||||
for env_var in necesasary_var_list:
|
||||
# ensure env var set
|
||||
assert (
|
||||
env_var in os.environ
|
||||
), (
|
||||
f"environment variable not set: {env_var}"
|
||||
)
|
||||
@@ -0,0 +1,21 @@
|
||||
"""Definition of setup_logging function."""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
|
||||
|
||||
def setup_logging() -> None:
|
||||
"""Setup logging."""
|
||||
requested_log_level = os.getenv('LOG_LEVEL', default='info')
|
||||
level = getattr(logging, requested_log_level.upper())
|
||||
fmt = (
|
||||
'%(asctime)s | '
|
||||
'%(levelname)s | '
|
||||
'%(filename)s | '
|
||||
'%(funcName)s | '
|
||||
'%(message)s'
|
||||
)
|
||||
datefmt = '%Y-%m-%d %H:%M:%S'
|
||||
logging.basicConfig(format=fmt, datefmt=datefmt, level=level)
|
||||
logging.debug('finished')
|
||||
-52
@@ -1,52 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from src.web import app
|
||||
|
||||
# prepare optional local setup
|
||||
env_path = Path(__file__).parent.parent / 'local.env'
|
||||
load_dotenv(env_path)
|
||||
|
||||
# ensure env vars set
|
||||
necesasary_var_list = {
|
||||
'MONGO_HOST',
|
||||
'MONGO_DB',
|
||||
'MONGO_COLLECTION',
|
||||
'MONGO_USER',
|
||||
'MONGO_PASSWORD',
|
||||
'DASH_AUTH_USERNAME',
|
||||
'DASH_AUTH_PASSWORD',
|
||||
}
|
||||
for env_var in necesasary_var_list:
|
||||
# ensure env var set
|
||||
assert (
|
||||
env_var in os.environ
|
||||
), (
|
||||
f"environment variable not set: {env_var}"
|
||||
)
|
||||
|
||||
# setup logging stream handler
|
||||
fmt = (
|
||||
'%(asctime)s | '
|
||||
'%(levelname)s | '
|
||||
'%(filename)s | '
|
||||
'%(funcName)s | '
|
||||
'%(message)s'
|
||||
)
|
||||
datefmt = '%Y-%m-%d %H:%M:%S'
|
||||
logging.basicConfig(format=fmt, datefmt=datefmt, level=logging.INFO)
|
||||
|
||||
logging.info('initialized app')
|
||||
server = app.server
|
||||
|
||||
if __name__ == '__main__':
|
||||
# prepare local env vars
|
||||
os.environ['MONGO_HOST'] = 'localhost'
|
||||
# run app
|
||||
app.run(debug=True)
|
||||
logging.info('started app')
|
||||
@@ -1 +0,0 @@
|
||||
from .classes import VisualSyntaxModelOutput
|
||||
@@ -1,89 +0,0 @@
|
||||
from pydantic import BaseModel, ValidationError
|
||||
from typing import List
|
||||
import random
|
||||
|
||||
|
||||
class OptionNotSetException(Exception):
|
||||
pass
|
||||
|
||||
|
||||
class ModelOutput(BaseModel):
|
||||
|
||||
@classmethod
|
||||
def classname(cls) -> str:
|
||||
"""Return classname."""
|
||||
return cls.__name__
|
||||
|
||||
@classmethod
|
||||
def list_fields(cls) -> List[str]:
|
||||
"""List options that are stored as attributes."""
|
||||
return list(cls.model_fields.keys())
|
||||
|
||||
@classmethod
|
||||
def from_random(cls):
|
||||
"""Instantiate with random numbers."""
|
||||
kwargs = {field: random.random() for field in cls.list_fields()}
|
||||
return cls(**kwargs)
|
||||
|
||||
@classmethod
|
||||
def from_choice(cls, option: str):
|
||||
"""Instantiate from choice."""
|
||||
if option is None:
|
||||
raise ValidationError()
|
||||
assert isinstance(option, str), "option is not a string"
|
||||
allowed_options_list = cls.list_fields()
|
||||
assert option in allowed_options_list, \
|
||||
f"{option} is not among allowed fields {allowed_options_list}"
|
||||
kwargs = {field: 0 for field in cls.list_fields()}
|
||||
kwargs[option] = 1
|
||||
return cls(**kwargs)
|
||||
|
||||
def __repr__(self) -> str:
|
||||
model_dict = self.model_dump()
|
||||
model_repr_str = f"{self.classname()}("
|
||||
model_repr_str += ", ".join([
|
||||
f"{field}={value:.3f}"
|
||||
for field, value
|
||||
in model_dict.items()
|
||||
])
|
||||
model_repr_str += ")"
|
||||
return model_repr_str
|
||||
|
||||
def highest_score_field(self) -> str:
|
||||
"""Return name of field with highest score."""
|
||||
model_dict = self.model_dump()
|
||||
return max(model_dict, key=lambda k: model_dict[k])
|
||||
|
||||
def highest_score_value(self) -> float:
|
||||
"""Return value of field with highest score."""
|
||||
model_dict = self.model_dump()
|
||||
return max(model_dict.values())
|
||||
|
||||
|
||||
class VisualSyntaxModelOutput(ModelOutput):
|
||||
non_transactional_action: float
|
||||
non_transactional_reaction: float
|
||||
unidirectional_transactional_action: float
|
||||
unidirectional_transactional_reaction: float
|
||||
bidirectional_transactional_action: float
|
||||
bidirectional_transactional_reaction: float
|
||||
conversion: float
|
||||
speech_process: float
|
||||
classification_overt_taxonomy: float
|
||||
analytical_exhaustive: float
|
||||
analytical_disarranged: float
|
||||
analytical_temporal: float
|
||||
analytical_distributed: float
|
||||
analytical_topological: float
|
||||
analytical_exploded: float
|
||||
analytical_inclusive: float
|
||||
symbolic_suggestive: float
|
||||
symbolic_attributive: float
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
m = VisualSyntaxModelOutput.from_random()
|
||||
print(m)
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
@@ -1,20 +0,0 @@
|
||||
CLASS_NAMES = [
|
||||
"non transactional action",
|
||||
"non transactional reaction",
|
||||
"unidirectional transactional action",
|
||||
"unidirectional transactional reaction",
|
||||
"bidirectional transactional action",
|
||||
"bidirectional transactional reaction",
|
||||
"conversion",
|
||||
"speech process",
|
||||
"classification overt taxonomy",
|
||||
"analytical exhaustive",
|
||||
"analytical disarranged",
|
||||
"analytical temporal",
|
||||
"analytical distributed",
|
||||
"anaytical topological",
|
||||
"analytical exploded",
|
||||
"analytical inclusive",
|
||||
"symbolic suggestive",
|
||||
"symbolic attributive"
|
||||
]
|
||||
@@ -1,9 +0,0 @@
|
||||
from .classes import (
|
||||
ContactModelOutput,
|
||||
AngleModelOutput,
|
||||
PointOfViewModelOutput,
|
||||
DistanceModelOutput,
|
||||
ModalityLightingModelOutput,
|
||||
ModalityColorModelOutput,
|
||||
ModalityDepthModelOutput
|
||||
)
|
||||
@@ -1,137 +0,0 @@
|
||||
from pydantic import BaseModel, ValidationError
|
||||
from typing import List
|
||||
import random
|
||||
|
||||
|
||||
class ModelOutput(BaseModel):
|
||||
|
||||
@classmethod
|
||||
def classname(cls) -> str:
|
||||
"""Return classname."""
|
||||
return cls.__name__
|
||||
|
||||
@classmethod
|
||||
def list_fields(cls) -> List[str]:
|
||||
"""List options that are stored as attributes."""
|
||||
return list(cls.model_fields.keys())
|
||||
|
||||
@classmethod
|
||||
def from_random(cls):
|
||||
"""Instantiate with random numbers."""
|
||||
kwargs = {field: random.random() for field in cls.list_fields()}
|
||||
return cls(**kwargs)
|
||||
|
||||
@classmethod
|
||||
def from_choice(cls, option: str):
|
||||
"""Instantiate from choice."""
|
||||
if option is None:
|
||||
raise ValidationError()
|
||||
assert isinstance(option, str)
|
||||
allowed_options_list = cls.list_fields()
|
||||
assert option in allowed_options_list, \
|
||||
f"{option} is not among allowed fields {allowed_options_list}"
|
||||
kwargs = {field: 0 for field in cls.list_fields()}
|
||||
kwargs[option] = 1
|
||||
return cls(**kwargs)
|
||||
|
||||
def __repr__(self) -> str:
|
||||
model_dict = self.model_dump()
|
||||
model_repr_str = f"{self.classname()}("
|
||||
model_repr_str += ", ".join([
|
||||
f"{field}={value:.3f}"
|
||||
for field, value
|
||||
in model_dict.items()
|
||||
])
|
||||
model_repr_str += ")"
|
||||
return model_repr_str
|
||||
|
||||
def highest_score_field(self) -> str:
|
||||
"""Return name of field with highest score."""
|
||||
model_dict = self.model_dump()
|
||||
return max(model_dict, key=lambda k: model_dict[k])
|
||||
|
||||
def highest_score_value(self) -> float:
|
||||
"""Return value of field with highest score."""
|
||||
model_dict = self.model_dump()
|
||||
return max(model_dict.values())
|
||||
|
||||
|
||||
class ContactModelOutput(ModelOutput):
|
||||
offer: float
|
||||
demand: float
|
||||
|
||||
|
||||
class AngleModelOutput(ModelOutput):
|
||||
high: float
|
||||
eye_level: float
|
||||
low: float
|
||||
|
||||
|
||||
class PointOfViewModelOutput(ModelOutput):
|
||||
frontal: float
|
||||
oblique: float
|
||||
|
||||
|
||||
class DistanceModelOutput(ModelOutput):
|
||||
long: float
|
||||
medium: float
|
||||
close: float
|
||||
|
||||
|
||||
class ModalityLightingModelOutput(ModelOutput):
|
||||
high: float
|
||||
medium: float
|
||||
low: float
|
||||
|
||||
|
||||
class ModalityColorModelOutput(ModelOutput):
|
||||
high: float
|
||||
medium: float
|
||||
low: float
|
||||
|
||||
|
||||
class ModalityDepthModelOutput(ModelOutput):
|
||||
high: float
|
||||
medium: float
|
||||
low: float
|
||||
|
||||
|
||||
# class InterpersonalModelOutput(BaseModel):
|
||||
# contact: ContactModelOutput
|
||||
# angle: AngleModelOutput
|
||||
# point_of_view: PointOfViewModelOutput
|
||||
# distance: DistanceModelOutput
|
||||
# modality_lighting: ModalityLightingModelOutput
|
||||
# modality_color: ModalityColorModelOutput
|
||||
# modality_depth: ModalityDepthModelOutput
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
m = ContactModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
m = AngleModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
m = PointOfViewModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
m = DistanceModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
m = ModalityLightingModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
m = ModalityColorModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
m = ModalityDepthModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
@@ -1,36 +0,0 @@
|
||||
|
||||
model_labels = {
|
||||
"contact": [
|
||||
"offer",
|
||||
"demand"
|
||||
],
|
||||
"angle": [
|
||||
"high",
|
||||
"eye-level",
|
||||
"low"
|
||||
],
|
||||
"point-of-view": [
|
||||
"frontal",
|
||||
"oblique"
|
||||
],
|
||||
"distance": [
|
||||
"long",
|
||||
"medium",
|
||||
"close"
|
||||
],
|
||||
"modality lighting": [
|
||||
"high",
|
||||
"medium",
|
||||
"low"
|
||||
],
|
||||
"modality color": [
|
||||
"high",
|
||||
"medium",
|
||||
"low"
|
||||
],
|
||||
"modality depth": [
|
||||
"high",
|
||||
"medium",
|
||||
"low"
|
||||
]
|
||||
}
|
||||
@@ -1,5 +0,0 @@
|
||||
from .classes import (
|
||||
InformationValueModelOutput,
|
||||
FramingModelOutput,
|
||||
SalienceModelOutput
|
||||
)
|
||||
@@ -1,92 +0,0 @@
|
||||
from pydantic import BaseModel, ValidationError
|
||||
from typing import List
|
||||
import random
|
||||
|
||||
|
||||
class ModelOutput(BaseModel):
|
||||
|
||||
@classmethod
|
||||
def classname(cls) -> str:
|
||||
"""Return classname."""
|
||||
return cls.__name__
|
||||
|
||||
@classmethod
|
||||
def list_fields(cls) -> List[str]:
|
||||
"""List options that are stored as attributes."""
|
||||
return list(cls.model_fields.keys())
|
||||
|
||||
@classmethod
|
||||
def from_random(cls):
|
||||
"""Instantiate with random numbers."""
|
||||
kwargs = {field: random.random() for field in cls.list_fields()}
|
||||
return cls(**kwargs)
|
||||
|
||||
@classmethod
|
||||
def from_choice(cls, option: str):
|
||||
"""Instantiate from choice."""
|
||||
if option is None:
|
||||
raise ValidationError()
|
||||
assert isinstance(option, str)
|
||||
allowed_options_list = cls.list_fields()
|
||||
assert option in allowed_options_list, \
|
||||
f"{option} is not among allowed fields {allowed_options_list}"
|
||||
kwargs = {field: 0 for field in cls.list_fields()}
|
||||
kwargs[option] = 1
|
||||
return cls(**kwargs)
|
||||
|
||||
def __repr__(self) -> str:
|
||||
model_dict = self.model_dump()
|
||||
model_repr_str = f"{self.classname()}("
|
||||
model_repr_str += ", ".join([
|
||||
f"{field}={value:.3f}"
|
||||
for field, value
|
||||
in model_dict.items()
|
||||
])
|
||||
model_repr_str += ")"
|
||||
return model_repr_str
|
||||
|
||||
def highest_score_field(self) -> str:
|
||||
"""Return name of field with highest score."""
|
||||
model_dict = self.model_dump()
|
||||
return max(model_dict, key=lambda k: model_dict[k])
|
||||
|
||||
def highest_score_value(self) -> float:
|
||||
"""Return value of field with highest score."""
|
||||
model_dict = self.model_dump()
|
||||
return max(model_dict.values())
|
||||
|
||||
|
||||
class InformationValueModelOutput(ModelOutput):
|
||||
given_new: float
|
||||
ideal_real: float
|
||||
central_marginal: float
|
||||
|
||||
|
||||
class FramingModelOutput(ModelOutput):
|
||||
frame_lines: float
|
||||
empty_space: float
|
||||
colour_contrast: float
|
||||
form_contrast: float
|
||||
|
||||
|
||||
class SalienceModelOutput(ModelOutput):
|
||||
size: float
|
||||
colour: float
|
||||
tone: float
|
||||
form: float
|
||||
positioning: float
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
m = InformationValueModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
m = FramingModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
m = SalienceModelOutput.from_random()
|
||||
print(repr(m))
|
||||
print(m.highest_score_field())
|
||||
print(m.highest_score_value())
|
||||
@@ -1,21 +0,0 @@
|
||||
|
||||
model_labels = {
|
||||
"information value": [
|
||||
"given-new",
|
||||
"ideal-real",
|
||||
"central-marginal"
|
||||
],
|
||||
"framing": [
|
||||
"frame lines",
|
||||
"empty space",
|
||||
"colour contrast",
|
||||
"form contrast"
|
||||
],
|
||||
"salience": [
|
||||
"size",
|
||||
"colour",
|
||||
"tone",
|
||||
"form",
|
||||
"positioning"
|
||||
]
|
||||
}
|
||||
@@ -1,4 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from src.web.app import app
|
||||
from src.web.app import server
|
||||
-247
@@ -1,247 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
|
||||
import dash_bootstrap_components as dbc
|
||||
from dash import ALL
|
||||
from dash import Dash
|
||||
from dash import Input
|
||||
from dash import Output
|
||||
from dash import State
|
||||
from dash_auth import BasicAuth
|
||||
from pydantic import ValidationError
|
||||
|
||||
from .layout import app_layout
|
||||
from core.database import connect
|
||||
from core.database import count_documents
|
||||
from core.database import get_visual_communication
|
||||
from core.database import NoDocumentFoundException
|
||||
from core.database import upsert_annotation
|
||||
from core.database import upsert_visual_communication
|
||||
from core.database import VisualCommunication
|
||||
from core.dto import ModelData
|
||||
|
||||
# setup app
|
||||
app = Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
|
||||
app.title = 'visual critical discourse analysis'.title()
|
||||
app.layout = app_layout
|
||||
server = app.server
|
||||
|
||||
# setup authentication
|
||||
AUTH_DICT = {
|
||||
os.getenv('DASH_AUTH_USERNAME'): os.getenv('DASH_AUTH_PASSWORD'),
|
||||
}
|
||||
BasicAuth(app, AUTH_DICT)
|
||||
|
||||
# connect to database
|
||||
collection, db, client = connect()
|
||||
|
||||
|
||||
# define callbacks
|
||||
@app.callback(
|
||||
Output('alert-element', 'is_open'),
|
||||
Output('alert-element', 'children'),
|
||||
Input('alert-message', 'data'),
|
||||
)
|
||||
def show_alert(
|
||||
msg: str | None,
|
||||
):
|
||||
if msg is None or msg == '':
|
||||
return False, ''
|
||||
logging.info(f'updated alert message: {msg}')
|
||||
return True, msg
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output('success-element', 'is_open'),
|
||||
Output('success-element', 'children'),
|
||||
Input('success-message', 'data'),
|
||||
)
|
||||
def show_success(
|
||||
msg: str | None,
|
||||
):
|
||||
if msg is None or msg == '':
|
||||
return False, ''
|
||||
logging.info(f"updated success message: {msg}")
|
||||
return True, msg
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output('progress-bar', 'value'),
|
||||
Output('progress-bar', 'max'),
|
||||
Output('progress-bar', 'label'),
|
||||
Input('next-button', 'n_clicks'),
|
||||
Input('upload-data', 'filename'),
|
||||
)
|
||||
def update_progress_bar(
|
||||
n_clicks: int,
|
||||
filename_list: list[str] | None,
|
||||
):
|
||||
logging.info('began updating progress bar')
|
||||
global collection
|
||||
# get values from database
|
||||
num_total = count_documents(
|
||||
collection=collection,
|
||||
only_with_annotation=False,
|
||||
)
|
||||
num_handled = count_documents(
|
||||
collection=collection,
|
||||
only_with_annotation=True,
|
||||
)
|
||||
limit = int(num_total/20)
|
||||
label_str = f"{num_handled}/{num_total}" if num_handled >= limit else ''
|
||||
return num_handled, num_total, label_str
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output('success-message', 'data', allow_duplicate=True),
|
||||
Output('alert-message', 'data', allow_duplicate=True),
|
||||
Input('upload-data', 'contents'),
|
||||
State('upload-data', 'filename'),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def upload_images(
|
||||
content_list: list[str] | None,
|
||||
filename_list: list[str] | None,
|
||||
):
|
||||
logging.info('began uploading images')
|
||||
global collection
|
||||
# stop early if possible
|
||||
if content_list is None or filename_list is None:
|
||||
logging.warning('content_list is None -> nothing to upload')
|
||||
return None, 'nothing selected to upload'.title()
|
||||
# build list of visual communication
|
||||
visual_communication_list = []
|
||||
for content, filename in zip(content_list, filename_list):
|
||||
try:
|
||||
image = VisualCommunication.decode_image(content)
|
||||
vis_com = VisualCommunication(
|
||||
name=filename,
|
||||
image=image,
|
||||
)
|
||||
except Exception as exc:
|
||||
logging.warning(
|
||||
(
|
||||
'failed creating VisualCommunication object '
|
||||
f"from file {filename}"
|
||||
),
|
||||
exc,
|
||||
)
|
||||
else:
|
||||
visual_communication_list.append(vis_com)
|
||||
# upsert documents
|
||||
success = upsert_visual_communication(
|
||||
collection=collection,
|
||||
visual_communication_list=visual_communication_list,
|
||||
)
|
||||
if success:
|
||||
logging.info(f"succesfully uploaded {len(filename_list)} images")
|
||||
return 'successfully uploaded images'.title(), None
|
||||
logging.warning('failed inserting images into database')
|
||||
return None, 'failed uploading images'.title()
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output('alert-message', 'data', allow_duplicate=True),
|
||||
Output('vis-com-name', 'data'),
|
||||
Output('image-container', 'src'),
|
||||
Output({'type': 'annotation', 'index': ALL}, 'value'),
|
||||
Input('next-button', 'n_clicks'),
|
||||
State('vis-com-name', 'data'),
|
||||
State('image-container', 'src'),
|
||||
State({'type': 'annotation', 'index': ALL}, 'id'),
|
||||
State({'type': 'annotation', 'index': ALL}, 'value'),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def cycle_visual_communication_data(
|
||||
n_clicks: int,
|
||||
vis_com_name: str,
|
||||
image_src: str,
|
||||
annotation_keys: list,
|
||||
annotation_values: list,
|
||||
):
|
||||
logging.info('began cycling visual communication data')
|
||||
global collection
|
||||
# prepare default response
|
||||
response = [
|
||||
'',
|
||||
vis_com_name,
|
||||
image_src,
|
||||
annotation_values,
|
||||
]
|
||||
# check if next-button clicked
|
||||
if n_clicks == 0:
|
||||
logging.info('stopping early: next-button has not yet been clicked')
|
||||
return response
|
||||
# check if visual communication name is set
|
||||
if len(vis_com_name) > 0:
|
||||
logging.info('saving annotations to database: %s', vis_com_name)
|
||||
try:
|
||||
# extract option keys
|
||||
annotation_keys = [
|
||||
elem['index']
|
||||
for elem in annotation_keys
|
||||
]
|
||||
# ensure all options are set
|
||||
logging.info(annotation_keys)
|
||||
for option, value in zip(annotation_keys, annotation_values):
|
||||
if value is None:
|
||||
raise ValueError(f"{option} is not set")
|
||||
# prepare data to save
|
||||
annotation_keys = [
|
||||
elem.replace(' ', '_')
|
||||
for elem
|
||||
in annotation_keys
|
||||
]
|
||||
annotation_values = [
|
||||
elem.replace(' ', '_').lower()
|
||||
for elem
|
||||
in annotation_values
|
||||
]
|
||||
annotation_map = {
|
||||
key: value
|
||||
for key, value
|
||||
in zip(annotation_keys, annotation_values)
|
||||
}
|
||||
# instantiate ModelOutputs object
|
||||
annotations = ModelData.from_annotations(**annotation_map)
|
||||
# save data to database
|
||||
upsert_annotation(
|
||||
collection=collection,
|
||||
vis_com_name=vis_com_name,
|
||||
annotations=annotations,
|
||||
)
|
||||
except (ValueError, ValidationError) as exc:
|
||||
msg = f"failed saving annotation: {exc}"
|
||||
logging.warning(msg)
|
||||
response[0] = msg
|
||||
return tuple(response)
|
||||
# get new visual communication
|
||||
logging.info('trying to get new visual communication')
|
||||
try:
|
||||
# get data
|
||||
vis_com = get_visual_communication(
|
||||
collection=collection,
|
||||
with_annotation=False,
|
||||
)
|
||||
# set variables
|
||||
vis_com_name = vis_com.name
|
||||
image_src = vis_com.webencoded_image()
|
||||
if vis_com.prediction is not None:
|
||||
# TODO: update to use optional predictions
|
||||
pass
|
||||
else:
|
||||
# reset annotations
|
||||
annotation_values = [None for elem in annotation_values]
|
||||
except NoDocumentFoundException:
|
||||
msg = 'no unannotated data in database'
|
||||
logging.warning(msg)
|
||||
response[0] = msg
|
||||
return tuple(response)
|
||||
else:
|
||||
response[1] = vis_com_name
|
||||
response[2] = image_src
|
||||
response[3] = annotation_values
|
||||
logging.info('finished getting visual communication: %s', vis_com_name)
|
||||
return tuple(response)
|
||||
@@ -1 +0,0 @@
|
||||
from .layout import app_layout
|
||||
@@ -1,21 +0,0 @@
|
||||
import dash_mantine_components as dmc
|
||||
from dash import html
|
||||
from pathlib import Path
|
||||
from base64 import b64encode
|
||||
|
||||
# read init img
|
||||
init_img_path = Path(__file__).parent / "init_img.png"
|
||||
with open(init_img_path.absolute(), "rb") as fh:
|
||||
init_img_enc = b64encode(fh.read()).decode("utf-8")
|
||||
# generate init img string
|
||||
init_img_src = f"data:image/png;base64, {init_img_enc}"
|
||||
|
||||
image_element = dmc.Center(
|
||||
html.Img(
|
||||
style={
|
||||
"width": "100%",
|
||||
},
|
||||
id="image-container",
|
||||
src=init_img_src
|
||||
)
|
||||
)
|
||||
@@ -2,7 +2,7 @@ from __future__ import annotations
|
||||
|
||||
from pathlib import Path
|
||||
|
||||
from core.database.classes import VisualCommunication
|
||||
from shared.database.classes import VisualCommunication
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
||||
@@ -5,8 +5,8 @@ from pathlib import Path
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from core.database import connect
|
||||
from core.database import get_visual_communication
|
||||
from shared.database import connect
|
||||
from shared.database import get_visual_communication
|
||||
|
||||
if __name__ == '__main__':
|
||||
# prepare env vars
|
||||
|
||||
@@ -5,8 +5,8 @@ from pathlib import Path
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from core.database import connect
|
||||
from core.database.classes import VisualCommunication
|
||||
from shared.database import connect
|
||||
from shared.database.classes import VisualCommunication
|
||||
|
||||
if __name__ == '__main__':
|
||||
# prepare env vars
|
||||
|
||||
@@ -6,8 +6,8 @@ from pathlib import Path
|
||||
from dotenv import load_dotenv
|
||||
from pymongo.errors import DuplicateKeyError
|
||||
|
||||
from core.database import connect
|
||||
from core.database.classes import VisualCommunication
|
||||
from shared.database import connect
|
||||
from shared.database.classes import VisualCommunication
|
||||
|
||||
if __name__ == '__main__':
|
||||
# get list of image paths
|
||||
|
||||
@@ -5,8 +5,8 @@ from pathlib import Path
|
||||
from dotenv import load_dotenv
|
||||
from pymongo.errors import DuplicateKeyError
|
||||
|
||||
from core.database import connect
|
||||
from core.database import VisualCommunication
|
||||
from shared.database import connect
|
||||
from shared.database import VisualCommunication
|
||||
|
||||
if __name__ == '__main__':
|
||||
# get list of image paths
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from core.dto import ModelData
|
||||
from shared.dto import ModelData
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
@@ -11,6 +11,9 @@ if __name__ == '__main__':
|
||||
in range(3)
|
||||
]
|
||||
# generate random predictions
|
||||
[vis_com.generate_random_prediction() for vis_com in vis_com_list]
|
||||
[
|
||||
vis_com.from_random()
|
||||
for vis_com in vis_com_list
|
||||
]
|
||||
for vis_com in vis_com_list:
|
||||
print(vis_com)
|
||||
|
||||
@@ -6,9 +6,9 @@ from pathlib import Path
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from core.database import connect
|
||||
from core.database import upsert_predictions
|
||||
from core.database.classes import VisualCommunication
|
||||
from shared.database import connect
|
||||
from shared.database import upsert_prediction
|
||||
from shared.database.classes import VisualCommunication
|
||||
|
||||
if __name__ == '__main__':
|
||||
# setup logging
|
||||
@@ -45,7 +45,7 @@ if __name__ == '__main__':
|
||||
for vis_com in vis_com_list:
|
||||
if vis_com.prediction is None:
|
||||
continue
|
||||
upsert_predictions(
|
||||
upsert_prediction(
|
||||
collection=collection,
|
||||
vis_com_name=vis_com.name,
|
||||
predictions=vis_com.prediction,
|
||||
|
||||
@@ -5,8 +5,8 @@ from pathlib import Path
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from core.database import connect
|
||||
from core.database import total_documents
|
||||
from shared.database import connect
|
||||
from shared.database import count_documents
|
||||
|
||||
if __name__ == '__main__':
|
||||
# prepare env vars
|
||||
@@ -17,7 +17,8 @@ if __name__ == '__main__':
|
||||
# connect to database
|
||||
collection, db, client = connect()
|
||||
# get visual communication
|
||||
num_docs = total_documents(
|
||||
num_docs = count_documents(
|
||||
collection=collection,
|
||||
only_with_annotation=True,
|
||||
)
|
||||
print(f"number of annotated documents in database: {num_docs}")
|
||||
|
||||
@@ -5,8 +5,8 @@ from pathlib import Path
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
from core.database import connect
|
||||
from core.database import total_documents
|
||||
from shared.database import connect
|
||||
from shared.database import count_documents
|
||||
|
||||
if __name__ == '__main__':
|
||||
# prepare env vars
|
||||
@@ -17,7 +17,8 @@ if __name__ == '__main__':
|
||||
# connect to database
|
||||
collection, db, client = connect()
|
||||
# get visual communication
|
||||
num_docs = total_documents(
|
||||
num_docs = count_documents(
|
||||
collection=collection,
|
||||
only_with_annotation=False,
|
||||
)
|
||||
print(f"total number of documents in database: {num_docs}")
|
||||
|
||||
@@ -1,9 +1,5 @@
|
||||
###########
|
||||
# BUILDER #
|
||||
###########
|
||||
|
||||
# pull official base image
|
||||
FROM python:3.12-slim-bullseye as BUILDER
|
||||
# build stage
|
||||
FROM python:3.12-slim-bookworm as BUILDER
|
||||
|
||||
# set environment variables
|
||||
ENV PYTHONUNBUFFERED=1 \
|
||||
@@ -33,15 +29,12 @@ ENV PATH="${POETRY_HOME}/bin:$PATH"
|
||||
|
||||
# install runtime dependencies
|
||||
WORKDIR ${APP_HOME}
|
||||
COPY poetry.lock pyproject.toml ./
|
||||
RUN --mount=type=cache,target=${POETRY_CACHE_DIR} poetry install
|
||||
COPY ../poetry.lock ../pyproject.toml ./
|
||||
RUN --mount=type=cache,target=${POETRY_CACHE_DIR} poetry install \
|
||||
--with shared,web_ui
|
||||
|
||||
#########
|
||||
# FINAL #
|
||||
#########
|
||||
|
||||
# pull official base image
|
||||
FROM python:3.12-slim-bullseye
|
||||
# final stage
|
||||
FROM python:3.12-slim-bookworm
|
||||
|
||||
# copy virtualenv made by poetry
|
||||
ENV APP_HOME=/home/app \
|
||||
@@ -56,8 +49,8 @@ RUN mkdir -p /home/app && \
|
||||
|
||||
# add code while changing ownership
|
||||
WORKDIR $APP_HOME
|
||||
COPY --chown=app:app ../shared ./shared
|
||||
COPY --chown=app:app ./src ./src
|
||||
COPY --chown=app:app ./core ./core
|
||||
|
||||
# change to the app user
|
||||
USER app
|
||||
@@ -0,0 +1,13 @@
|
||||
services:
|
||||
web_ui:
|
||||
image: visual_critical_discourse_analysis:test
|
||||
container_name: visual_critical_discourse_analysis_alone
|
||||
build:
|
||||
context: ../
|
||||
dockerfile: Dockerfile.web_ui
|
||||
ports:
|
||||
- 8050:8050
|
||||
env_file:
|
||||
- ../server.env
|
||||
environment:
|
||||
- ENV=TEST
|
||||
@@ -0,0 +1,3 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from .init_app import init_app
|
||||
@@ -0,0 +1,260 @@
|
||||
"""Definition of init_app function."""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
|
||||
import dash_bootstrap_components as dbc
|
||||
from dash import ALL
|
||||
from dash import Dash
|
||||
from dash import Input
|
||||
from dash import Output
|
||||
from dash import State
|
||||
from dash_auth import BasicAuth
|
||||
from pydantic import ValidationError
|
||||
from pymongo.collection import Collection
|
||||
|
||||
from .layout import app_layout
|
||||
from shared.database import count_documents
|
||||
from shared.database import get_visual_communication
|
||||
from shared.database import NoDocumentFoundException
|
||||
from shared.database import upsert_annotation
|
||||
from shared.database import upsert_visual_communication
|
||||
from shared.database import VisualCommunication
|
||||
from shared.dto import ModelData
|
||||
|
||||
|
||||
def init_app(
|
||||
collection: Collection,
|
||||
) -> Dash:
|
||||
"""Initialise web UI application."""
|
||||
# setup app
|
||||
app = Dash(
|
||||
name='visual_critical_discourse_analysis_web_ui',
|
||||
external_stylesheets=[
|
||||
dbc.themes.BOOTSTRAP,
|
||||
],
|
||||
)
|
||||
app.title = 'visual critical discourse analysis'.title()
|
||||
app.layout = app_layout
|
||||
|
||||
# setup authentication
|
||||
auth_dict = {
|
||||
os.getenv('DASH_AUTH_USERNAME'): os.getenv('DASH_AUTH_PASSWORD'),
|
||||
}
|
||||
BasicAuth(app, auth_dict)
|
||||
|
||||
# define callback: show warning
|
||||
@app.callback(
|
||||
Output('warning-element', 'is_open'),
|
||||
Output('warning-element', 'children'),
|
||||
Input('warning-message', 'data'),
|
||||
)
|
||||
def show_warning(
|
||||
msg: str | None,
|
||||
) -> tuple[bool, str]:
|
||||
"""Show warning message in web ui."""
|
||||
if msg is None or msg == '':
|
||||
return False, ''
|
||||
logging.debug('updated warning message: %s', msg)
|
||||
return True, msg
|
||||
|
||||
# define callback: show info
|
||||
@app.callback(
|
||||
Output('info-element', 'is_open'),
|
||||
Output('info-element', 'children'),
|
||||
Input('info-message', 'data'),
|
||||
)
|
||||
def show_info(
|
||||
msg: str | None,
|
||||
) -> tuple[bool, str]:
|
||||
"""Show info message in web ui."""
|
||||
if msg is None or msg == '':
|
||||
return False, ''
|
||||
logging.debug('updated info message: %s', msg)
|
||||
return True, msg
|
||||
|
||||
# define callback: update progress bar
|
||||
@app.callback(
|
||||
Output('progress-bar', 'value'),
|
||||
Output('progress-bar', 'max'),
|
||||
Output('progress-bar', 'label'),
|
||||
Input('next-button', 'n_clicks'),
|
||||
Input('upload-data', 'filename'),
|
||||
)
|
||||
def update_progress_bar(
|
||||
n_clicks: int,
|
||||
filename_list: list[str] | None,
|
||||
) -> tuple[int, int, str]:
|
||||
"""Update progress bar in web ui."""
|
||||
assert isinstance(n_clicks, int)
|
||||
if filename_list is not None:
|
||||
assert isinstance(filename_list, list)
|
||||
# get values from database
|
||||
num_total = count_documents(
|
||||
collection=collection,
|
||||
only_with_annotation=False,
|
||||
)
|
||||
num_handled = count_documents(
|
||||
collection=collection,
|
||||
only_with_annotation=True,
|
||||
)
|
||||
limit = int(num_total/20)
|
||||
label_str = f"{
|
||||
num_handled
|
||||
}/{num_total}" if num_handled >= limit else ''
|
||||
return num_handled, num_total, label_str
|
||||
|
||||
# define callback: upload image
|
||||
@app.callback(
|
||||
Output('info-message', 'data', allow_duplicate=True),
|
||||
Output('warning-message', 'data', allow_duplicate=True),
|
||||
Input('upload-data', 'contents'),
|
||||
State('upload-data', 'filename'),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def upload_images(
|
||||
content_list: list[str] | None,
|
||||
filename_list: list[str] | None,
|
||||
) -> tuple[str | None, str | None]:
|
||||
"""Upload image to database through web ui."""
|
||||
# stop early if possible
|
||||
if content_list is None or filename_list is None:
|
||||
logging.info('nothing to upload.')
|
||||
return None, 'nothing to upload'.title()
|
||||
# build list of visual communication
|
||||
vis_com_list = []
|
||||
for content, filename in zip(content_list, filename_list):
|
||||
try:
|
||||
image = VisualCommunication.decode_image(content=content)
|
||||
vis_com = VisualCommunication(
|
||||
name=filename,
|
||||
image=image,
|
||||
)
|
||||
except Exception as exc:
|
||||
logging.error('failed handling data from file: %s', filename)
|
||||
logging.debug(exc)
|
||||
continue
|
||||
vis_com_list.append(vis_com)
|
||||
# upsert documents
|
||||
success = upsert_visual_communication(
|
||||
collection=collection,
|
||||
visual_communication_list=vis_com_list,
|
||||
)
|
||||
if success:
|
||||
logging.info('uploaded %s files to database', len(vis_com_list))
|
||||
return 'successfully uploaded images'.title(), None
|
||||
logging.error('failed uploading images to database')
|
||||
return None, 'failed uploading images'.title()
|
||||
|
||||
# define callback: cycle visual communication data
|
||||
@app.callback(
|
||||
Output('warning-message', 'data', allow_duplicate=True),
|
||||
Output('vis-com-name', 'data'),
|
||||
Output('image-container', 'src'),
|
||||
Output({'type': 'annotation', 'index': ALL}, 'value'),
|
||||
Input('next-button', 'n_clicks'),
|
||||
State('vis-com-name', 'data'),
|
||||
State('image-container', 'src'),
|
||||
State({'type': 'annotation', 'index': ALL}, 'id'),
|
||||
State({'type': 'annotation', 'index': ALL}, 'value'),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def cycle_vis_com_data(
|
||||
n_clicks: int,
|
||||
vis_com_name: str,
|
||||
image_src: str,
|
||||
annotation_keys: list,
|
||||
annotation_values: list,
|
||||
) -> tuple:
|
||||
"""Cycle visual communcation data."""
|
||||
assert isinstance(n_clicks, int)
|
||||
assert isinstance(vis_com_name, str)
|
||||
assert isinstance(image_src, str)
|
||||
assert isinstance(annotation_keys, list)
|
||||
assert isinstance(annotation_values, list)
|
||||
# prepare default response
|
||||
response = [
|
||||
'',
|
||||
vis_com_name,
|
||||
image_src,
|
||||
annotation_values,
|
||||
]
|
||||
# stop early if possible
|
||||
if n_clicks == 0:
|
||||
return tuple(response)
|
||||
# check if visual communication name is set
|
||||
if len(vis_com_name) > 0:
|
||||
logging.info('saving annotations to database: %s', vis_com_name)
|
||||
try:
|
||||
# extract option keys
|
||||
annotation_keys = [
|
||||
elem['index']
|
||||
for elem in annotation_keys
|
||||
]
|
||||
# ensure all options are set
|
||||
logging.info(annotation_keys)
|
||||
for option, value in zip(annotation_keys, annotation_values):
|
||||
if value is None:
|
||||
raise ValueError(f"{option} is not set")
|
||||
# prepare data to save
|
||||
annotation_keys = [
|
||||
elem.replace(' ', '_')
|
||||
for elem
|
||||
in annotation_keys
|
||||
]
|
||||
annotation_values = [
|
||||
elem.replace(' ', '_').lower()
|
||||
for elem
|
||||
in annotation_values
|
||||
]
|
||||
annotation_map = {
|
||||
key: value
|
||||
for key, value
|
||||
in zip(annotation_keys, annotation_values)
|
||||
}
|
||||
# instantiate ModelOutputs object
|
||||
annotations = ModelData.from_annotations(**annotation_map)
|
||||
# save data to database
|
||||
upsert_annotation(
|
||||
collection=collection,
|
||||
vis_com_name=vis_com_name,
|
||||
annotations=annotations,
|
||||
)
|
||||
except (ValueError, ValidationError) as exc:
|
||||
msg = f"failed saving annotation: {exc}"
|
||||
logging.warning(msg)
|
||||
response[0] = msg
|
||||
return tuple(response)
|
||||
# get new visual communication
|
||||
logging.info('trying to get new visual communication')
|
||||
try:
|
||||
# get data
|
||||
vis_com = get_visual_communication(
|
||||
collection=collection,
|
||||
with_annotation=False,
|
||||
)
|
||||
# set variables
|
||||
vis_com_name = vis_com.name
|
||||
image_src = vis_com.webencoded_image()
|
||||
if vis_com.prediction is not None:
|
||||
# TODO: update to use optional predictions
|
||||
pass
|
||||
else:
|
||||
# reset annotations
|
||||
annotation_values = [None for elem in annotation_values]
|
||||
except NoDocumentFoundException:
|
||||
msg = 'no unannotated data in database'
|
||||
logging.warning(msg)
|
||||
response[0] = msg
|
||||
return tuple(response)
|
||||
else:
|
||||
response[1] = vis_com_name
|
||||
response[2] = image_src
|
||||
response[3] = annotation_values
|
||||
logging.info(
|
||||
'finished getting visual communication: %s', vis_com_name,
|
||||
)
|
||||
return tuple(response)
|
||||
logging.info('initialised app')
|
||||
return app
|
||||
@@ -0,0 +1,3 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from .layout import app_layout
|
||||
@@ -1,3 +1,5 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import dash_mantine_components as dmc
|
||||
|
||||
from .image import image_element
|
||||
@@ -11,8 +13,8 @@ body_element = dmc.Container(
|
||||
grow=True,
|
||||
children=[
|
||||
dmc.Col([image_element], span=5),
|
||||
dmc.Col([inputs_element], span=7)
|
||||
dmc.Col([inputs_element], span=7),
|
||||
],
|
||||
)
|
||||
),
|
||||
],
|
||||
)
|
||||
@@ -0,0 +1,24 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from base64 import b64encode
|
||||
from pathlib import Path
|
||||
|
||||
import dash_mantine_components as dmc
|
||||
from dash import html
|
||||
|
||||
# read init img
|
||||
init_img_path = Path(__file__).parent / 'init_img.png'
|
||||
with open(init_img_path.absolute(), 'rb') as fh:
|
||||
init_img_enc = b64encode(fh.read()).decode('utf-8')
|
||||
# generate init img string
|
||||
init_img_src = f"data:image/png;base64, {init_img_enc}"
|
||||
|
||||
image_element = dmc.Center(
|
||||
html.Img(
|
||||
style={
|
||||
'width': '100%',
|
||||
},
|
||||
id='image-container',
|
||||
src=init_img_src,
|
||||
),
|
||||
)
|
||||
|
Before Width: | Height: | Size: 9.3 KiB After Width: | Height: | Size: 9.3 KiB |
@@ -1,23 +1,25 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import dash_mantine_components as dmc
|
||||
|
||||
from .labels import labels_element
|
||||
|
||||
next_button = dmc.Button(
|
||||
"next".title(),
|
||||
id="next-button",
|
||||
'next'.title(),
|
||||
id='next-button',
|
||||
n_clicks=0,
|
||||
fullWidth=True,
|
||||
color="lime",
|
||||
radius="sm",
|
||||
size="md",
|
||||
color='lime',
|
||||
radius='sm',
|
||||
size='md',
|
||||
style={
|
||||
"height": "50px"
|
||||
}
|
||||
'height': '50px',
|
||||
},
|
||||
)
|
||||
|
||||
inputs_element = dmc.SimpleGrid(
|
||||
children=[
|
||||
labels_element,
|
||||
next_button
|
||||
]
|
||||
next_button,
|
||||
],
|
||||
)
|
||||
@@ -4,17 +4,17 @@ import dash_mantine_components as dmc
|
||||
from dash import dcc
|
||||
from dash import html
|
||||
|
||||
from core.dto import AngleData
|
||||
from core.dto import ContactData
|
||||
from core.dto import DistanceData
|
||||
from core.dto import FramingData
|
||||
from core.dto import InformationValueData
|
||||
from core.dto import ModalityColorData
|
||||
from core.dto import ModalityDepthData
|
||||
from core.dto import ModalityLightingData
|
||||
from core.dto import PointOfViewData
|
||||
from core.dto import SalienceData
|
||||
from core.dto import VisualSyntaxData
|
||||
from shared.dto import AngleData
|
||||
from shared.dto import ContactData
|
||||
from shared.dto import DistanceData
|
||||
from shared.dto import FramingData
|
||||
from shared.dto import InformationValueData
|
||||
from shared.dto import ModalityColorData
|
||||
from shared.dto import ModalityDepthData
|
||||
from shared.dto import ModalityLightingData
|
||||
from shared.dto import PointOfViewData
|
||||
from shared.dto import SalienceData
|
||||
from shared.dto import VisualSyntaxData
|
||||
|
||||
|
||||
def generate_visual_syntax_options_map():
|
||||
@@ -1,22 +1,24 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import dash_mantine_components as dmc
|
||||
|
||||
from .stores import stores_element
|
||||
from .alerts import alerts_element
|
||||
from .header import header_element
|
||||
from .body import body_element
|
||||
from .header import header_element
|
||||
from .stores import stores_element
|
||||
|
||||
|
||||
app_layout = dmc.MantineProvider(
|
||||
theme={
|
||||
"fontFamily": '"Inter", sans-serif',
|
||||
"components": {
|
||||
"NavLink": {
|
||||
"styles": {
|
||||
"label": {
|
||||
"color": "#c2c7d0"
|
||||
}
|
||||
}
|
||||
}
|
||||
'fontFamily': '"Inter", sans-serif',
|
||||
'components': {
|
||||
'NavLink': {
|
||||
'styles': {
|
||||
'label': {
|
||||
'color': '#c2c7d0',
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
children=[
|
||||
@@ -27,8 +29,8 @@ app_layout = dmc.MantineProvider(
|
||||
header_element,
|
||||
body_element,
|
||||
],
|
||||
fluid=True
|
||||
fluid=True,
|
||||
),
|
||||
|
||||
]
|
||||
],
|
||||
)
|
||||
@@ -6,8 +6,8 @@ from dash import html
|
||||
|
||||
stores_element = html.Div(
|
||||
children=[
|
||||
dcc.Store(id='alert-message', data=''),
|
||||
dcc.Store(id='success-message', data=''),
|
||||
dcc.Store(id='warning-message', data=''),
|
||||
dcc.Store(id='info-message', data=''),
|
||||
dcc.Store(id='vis-com-name', data=''),
|
||||
],
|
||||
)
|
||||
@@ -0,0 +1,23 @@
|
||||
"""Definition of web_ui main script."""
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
|
||||
from .app import init_app
|
||||
from shared.database import connect
|
||||
from shared.utils import check_env
|
||||
from shared.utils import setup_logging
|
||||
|
||||
# ensure env vars set
|
||||
check_env()
|
||||
|
||||
# setup logging stream handler
|
||||
setup_logging()
|
||||
|
||||
# connect to database
|
||||
collection, db, client = connect()
|
||||
|
||||
# initialise application
|
||||
app = init_app(collection=collection)
|
||||
server = app.server
|
||||
server.config.update(SECRET_KEY=os.urandom(24))
|
||||
Reference in New Issue
Block a user