Move questions and optical flow to separate config files; clean up config.example.yaml
- questions: extracted from config.yaml into config/questions.yaml (committed, like optical_flow_config.yaml) - optical_flow_config_file and questions_config_file are now required fields - data_dir and out_dir are now required (no defaults) - filenames: trimmed to input-only in example; output filenames stay as code defaults - annotator: remove optional guard around optical flow config loading Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
55
README.md
55
README.md
@@ -21,6 +21,7 @@ cp config/clips.example.txt config/clips.txt
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# 3. Edit config/config.yaml (set data_dir and out_dir)
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# Edit config/clips.txt (list clips to annotate)
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# Edit config/questions.yaml to customise survey questions (optional)
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# 4. Run
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uv run python -m river_annotation_tool.annotation_script
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@@ -48,7 +49,7 @@ cp config/config.example.yaml config/config.yaml
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cp config/clips.example.txt config/clips.txt
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```
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Edit `config/config.yaml` to set your `data_dir` and `out_dir`, then edit `config/clips.txt` to list the clips you want to annotate. See the [Configuration](#configuration) section for all available options.
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Edit `config/config.yaml` to set your `data_dir` and `out_dir`, then edit `config/clips.txt` to list the clips you want to annotate. Survey questions are defined in `config/questions.yaml` (committed to the repo; edit to customise). See the [Configuration](#configuration) section for all available options.
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### S3 storage (optional)
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@@ -115,49 +116,38 @@ uv run python -m river_annotation_tool.annotation_script --clip left_20230615T12
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## Configuration
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All settings live in `config/config.yaml`. Copy `config/config.example.yaml` to get started.
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Main settings live in `config/config.yaml`. Copy `config/config.example.yaml` to get started.
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```yaml
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storage: local # required: 'local' or 's3'
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data_dir: data/clips # directory containing ZIP archives (local path or bucket/prefix for S3)
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out_dir: data/annotation_results
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data_dir: # required: directory containing ZIP archives (local path or bucket/prefix for S3)
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out_dir: # required: where to write annotations
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clips_file: config/clips.txt
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# optical_flow_config_file: config/optical_flow_config.yaml # optional, enables Auto Segment
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optical_flow_config_file: config/optical_flow_config.yaml
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questions_config_file: config/questions.yaml
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display_max: 720 # longest side in pixels for display
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fps_fallback: 25 # FPS to use if the video header is missing
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max_frames: 100 # max frames to extract per clip
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questions:
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- section: River
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items:
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- key: flow
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label: "Flow Regime"
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options: [Turbulent, Laminar, Uncertain]
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default: Laminar
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# add more items or sections as needed
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# Override input filenames only if your ZIP archives differ from the defaults
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filenames:
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video_in_zip: left.mp4 # video filename inside each ZIP archive
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video_tmp_suffix: .mp4 # suffix for the extraction temp file
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zip_extension: .zip # extension used when resolving clip names
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mask: mask.png # saved water mask
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metadata: metadata.json # saved survey answers
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frame: frame.png # middle frame snapshot
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overlay: overlay.png # frame with mask blended in green
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mask_vis: mask_vis.png # greyscale mask PNG (--extras only)
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gif_original_hires: video_original_hires.gif
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gif_original_lowres: video_original_lowres.gif
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gif_overlay_hires: video_overlay_hires.gif
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gif_overlay_lowres: video_overlay_lowres.gif
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video_in_zip: left.mp4
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video_tmp_suffix: .mp4
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zip_extension: .zip
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```
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Add, remove, or reorder questions directly in the YAML — the UI rebuilds automatically. `key` is what gets saved in `metadata.json`; `default` selects the pre-checked option (omit or set to `null` to leave unselected).
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Output filenames (`mask.png`, `metadata.json`, etc.) have sensible defaults and can be overridden in the `filenames:` block — see [`config.py`](src/river_annotation_tool/config.py) for the full list.
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### Optical flow segmentation (optional)
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### Survey questions
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Set `optical_flow_config_file` in `config.yaml` to point to a YAML file that enables the **Auto Segment** button. When pressed, the tool computes a river mask from the loaded frames and replaces the current mask (undoable). The segmentation combines two criteria:
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Survey questions are defined in `config/questions.yaml` (committed to the repo). Add, remove, or reorder sections and items — the UI rebuilds automatically. `key` is what gets saved in `metadata.json`; `default` selects the pre-checked option (omit or set to `null` to leave unselected).
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### Optical flow segmentation
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`config/optical_flow_config.yaml` controls the **Auto Segment** button. When pressed, the tool computes a river mask from the loaded frames and replaces the current mask (undoable). The segmentation combines two criteria:
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- **Optical flow magnitude** — pixels where the temporal median of frame-to-frame flow (scaled by FPS) exceeds a fraction of the maximum are considered moving water.
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- **Brightness** — pixels outside a brightness window are excluded (removes sky, saturated glare, etc.).
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@@ -245,7 +235,7 @@ Polygons are drawn as overlays and do not affect the mask until you use **Fill**
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| Action | How |
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|---|---|
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| Load mask from previous clip | **Load Prev Mask** — copies the saved mask of the previous clip onto the current one; undoable |
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| Optical flow first guess | **Auto Segment** — replaces the current mask with an automatic river segmentation; undoable. Only available when `optical_flow_config_file` is set in `config.yaml`. |
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| Optical flow first guess | **Auto Segment** — replaces the current mask with an automatic river segmentation; undoable. Disabled when `enabled: false` in `config/optical_flow_config.yaml`. |
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### Image display adjustments
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@@ -289,7 +279,7 @@ All output filenames can be overridden via the `filenames:` section in `config/c
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### Survey answers (`metadata.json`)
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Keys and values are determined by the `questions` section in `config/config.yaml`. With the default config:
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Keys and values are determined by `config/questions.yaml`. With the default questions:
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```json
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{
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@@ -332,7 +322,8 @@ config/
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config.example.yaml # Example config to copy and edit
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clips.txt # Your clip list (git-ignored, copy from example)
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clips.example.txt # Example clip list
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optical_flow_config.yaml # Optional optical flow parameters (enable via config.yaml)
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questions.yaml # Survey question definitions
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optical_flow_config.yaml # Optical flow parameters (set enabled: false to disable Auto Segment)
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src/river_annotation_tool/
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annotation_script.py # Entry point — argument parsing and app launch
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annotator.py # Main QMainWindow — orchestrates all components
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@@ -1,66 +1,21 @@
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# For local storage, set data_dir and out_dir to file-system paths:
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storage: local # 'local' (default) or 's3'
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data_dir: data/filtered_data
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out_dir: data/annotation_results
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# For S3 storage, set storage: s3 and use bucket/prefix paths:
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# storage: s3
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# data_dir: my-bucket/clips
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# out_dir: my-bucket/annotation_results
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# Credentials are read from env vars (copy .env.example to .env):
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storage: local # 'local' or 's3'
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# Required: set these to your actual paths (local path or bucket/prefix for S3)
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data_dir:
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out_dir:
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# For S3 credentials, copy .env.example to .env and fill in:
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# S3_ACCESS_KEY, S3_SECRET_ACCESS_KEY, S3_ENDPOINT_URL
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clips_file: config/clips.txt
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optical_flow_config_file: config/optical_flow_config.yaml
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questions_config_file: config/questions.yaml
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display_max: 720
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fps_fallback: 25
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max_frames: 100
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questions:
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- section: River
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items:
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- key: flow
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label: Flow Regime
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options: [Turbulent, Laminar, Uncertain]
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default: Laminar
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- key: shadows
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label: Strong Shadows
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options: [Yes, No, Uncertain]
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default: No
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- key: artifacts
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label: Artifacts on River
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options: [Yes, No, Uncertain]
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default: No
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- section: Scene
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items:
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- key: lighting
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label: Lighting
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options: [Day, Night, Uncertain]
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default: Day
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- key: exposure
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label: Exposure
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options: [Overexposed, Underexposed, Both, Normal, Uncertain]
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default: Normal
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- section: Weather
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items:
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- key: snowing
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label: Snowing
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options: [Yes, No, Uncertain]
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default: No
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- key: snow_on_ground
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label: Snow on Ground
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options: [Yes, No, Uncertain]
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default: No
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# Input filenames (override if your ZIP archives differ)
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filenames:
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video_in_zip: left.mp4
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video_tmp_suffix: .mp4
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zip_extension: .zip
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mask: mask.png
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metadata: metadata.json
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frame: frame.png
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overlay: overlay.png
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mask_vis: mask_vis.png
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gif_original_hires: video_original_hires.gif
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gif_original_lowres: video_original_lowres.gif
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gif_overlay_hires: video_overlay_hires.gif
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gif_overlay_lowres: video_overlay_lowres.gif
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34
config/questions.yaml
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34
config/questions.yaml
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@@ -0,0 +1,34 @@
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- section: River
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items:
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- key: flow
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label: Flow Regime
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options: [Turbulent, Laminar, Uncertain]
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default: Laminar
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- key: shadows
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label: Strong Shadows
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options: [Yes, No, Uncertain]
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default: No
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- key: artifacts
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label: Artifacts on River
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options: [Yes, No, Uncertain]
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default: No
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- section: Scene
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items:
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- key: lighting
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label: Lighting
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options: [Day, Night, Uncertain]
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default: Day
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- key: exposure
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label: Exposure
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options: [Overexposed, Underexposed, Both, Normal, Uncertain]
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default: Normal
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- section: Weather
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items:
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- key: snowing
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label: Snowing
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options: [Yes, No, Uncertain]
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default: No
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- key: snow_on_ground
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label: Snow on Ground
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options: [Yes, No, Uncertain]
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default: No
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@@ -43,11 +43,7 @@ class Annotator(QMainWindow):
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self.fs = fs
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self.out_dir = config.out_dir
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self.extras = extras
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self.of_cfg = (
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load_optical_flow_config(Path(config.optical_flow_config_file))
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if config.optical_flow_config_file
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else None
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)
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self.of_cfg = load_optical_flow_config(Path(config.optical_flow_config_file))
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self.selector = ClipSelector(
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data_dir=config.data_dir,
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@@ -171,7 +167,7 @@ class Annotator(QMainWindow):
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btn_redo = QPushButton("Redo")
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btn_load_prev_mask = QPushButton("Load Prev Mask")
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btn_auto_segment = QPushButton("Auto Segment")
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btn_auto_segment.setEnabled(self.of_cfg is not None and self.of_cfg.enabled)
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btn_auto_segment.setEnabled(self.of_cfg.enabled)
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row1 = QHBoxLayout()
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for b in [
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@@ -22,16 +22,17 @@ class FilenameConfig:
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@dataclass
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class AppConfig:
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storage: str # required: 'local' or 's3'
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storage: str
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data_dir: str
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out_dir: str
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optical_flow_config_file: str
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questions_config_file: str
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display_max: int = 480
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fps_fallback: int = 25
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max_frames: int = 100
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data_dir: str = "data/clips"
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out_dir: str = "data/annotation_results"
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clips_file: str = "config/clips.txt"
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optical_flow_config_file: str = ""
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questions: list = field(default_factory=list)
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filenames: FilenameConfig = field(default_factory=FilenameConfig)
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questions: list = field(default_factory=list, init=False)
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def get_questions(self):
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return [
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@@ -69,14 +70,25 @@ def load_optical_flow_config(path: Path) -> OpticalFlowConfig:
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return OpticalFlowConfig(**data)
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def load_questions_config(path: Path) -> list:
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with open(path) as f:
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return yaml.safe_load(f)
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def load_config(path: Path) -> AppConfig:
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with open(path) as f:
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data = yaml.safe_load(f)
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if "storage" not in data:
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raise ValueError(
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f"{path}: missing required field 'storage'. Set it to 'local' or 's3'."
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)
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for required in (
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"storage",
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"data_dir",
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"out_dir",
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"optical_flow_config_file",
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"questions_config_file",
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):
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if not data.get(required):
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raise ValueError(f"{path}: missing required field '{required}'.")
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fn_data = data.pop("filenames", {})
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cfg = AppConfig(**data)
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cfg.filenames = FilenameConfig(**fn_data)
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cfg.questions = load_questions_config(Path(cfg.questions_config_file))
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return cfg
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