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重构：将 Baseline.py 迁移至 baseline/ 目录，新增多模型对比脚本

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yukun-hh
2026-05-17 16:14:48 +08:00
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## Project
CNN-based garbage classification (4 classes: 厨余垃圾/可回收物/其他垃圾/有害垃圾). ResNet-34 architecture, ~21M params, 256×256 RGB input, ~900 lines across 8 Python files. No package structure.
CNN-based garbage classification (4 classes: 厨余垃圾/可回收物/其他垃圾/有害垃圾). ResNet-34 architecture, ~21M params, 256×256 RGB input, ~900 lines across 11 Python files. No package structure.
## Pipeline (order matters)
```bash
python Merge_classes.py # merges 265 → 4 classes, creates ../trash_division_data/ultimate_4_class/
python Train.py # trains the model, saves best_model.pth + training_log.csv
python Finetune.py # optional: freezes early layers, saves finetuned_model.pth + finetune_log.csv
python Evaluate.py # plots confusion matrix / ROC / PR curves from best_model.pth
python Curve.py # plots loss/f1/acc/lr curves from training_log.csv
python Merge_classes.py # merges 265 → 4 classes, creates ../trash_division_data/ultimate_4_class/
python Train.py # trains the model, saves best_model.pth + training_log.csv
python Finetune.py # optional: freezes early layers, saves finetuned_model.pth + finetune_log.csv
python Evaluate.py # plots confusion matrix / ROC / PR curves from best_model.pth
python Curve.py # plots loss/f1/acc/lr curves from training_log.csv
python baseline/VGG_KNN.py # VGG16 feature extraction + KNN baseline
python baseline/compare_models.py # compares multiple models (ROC + accuracy bar chart)
```
Also usable standalone: `python Model.py` prints `torchsummary` parameter summary.
## Dependencies
No `requirements.txt` — install manually: `torch`, `torchvision`, `tqdm`, `matplotlib`, `pandas`, `Pillow`, `torchsummary`. `Evaluate.py` additionally needs `scikit-learn`.
No `requirements.txt` — install manually: `torch`, `torchvision`, `tqdm`, `matplotlib`, `pandas`, `Pillow`, `torchsummary`. `Evaluate.py` and `baseline/*.py` additionally need `scikit-learn`.
## Data setup
@@ -26,7 +28,7 @@ Data expected **outside repo** at `../trash_division_data/` (sibling dir). `Merg
## .gitignore — whitelist pattern
`.gitignore` uses `*` (ignore everything) then un-ignores specific files with `!` patterns. **Any new file you add to the repo must be explicitly whitelisted** or it will be invisible to git. The current whitelist: `Dataloader.py`, `LICENSE`, `Merge_classes.py`, `Model.py`, `README.md`, `THIRD_PARTY_LICENSES.md`, `Train.py`, `.gitattributes`, `.gitignore`.
`.gitignore` uses `*` (ignore everything) then un-ignores specific files with `!` patterns. **Any new file you add to the repo must be explicitly whitelisted** or it will be invisible to git. The current whitelist includes: `Dataloader.py`, `LICENSE`, `Merge_classes.py`, `Model.py`, `README.md`, `THIRD_PARTY_LICENSES.md`, `Train.py`, `.gitattributes`, `.gitignore`, plus `Finetune.py`, `Curve.py`, `Evaluate.py`, `AGENTS.md`, 4× output PNG, `training_log.csv`, and `baseline/`.
`best_model.pth` and `finetuned_model.pth` are **untracked** (~125 MB each) — back them up manually if needed. `Finetune.py`, `Curve.py`, `Evaluate.py`, `AGENTS.md`, `training_log*.csv`, and `finetune_log.csv` are also untracked (not in whitelist).
@@ -60,6 +62,16 @@ Data expected **outside repo** at `../trash_division_data/` (sibling dir). `Merg
- Saves `confusion_matrix.png`, `roc_curve.png`, `pr_curve.png`
- Requires `scikit-learn`
### baseline/ (VGG_KNN.py + compare_models.py)
- `baseline/VGG_KNN.py` can run standalone (`python baseline/VGG_KNN.py`) or be imported from `compare_models.py`
- Uses `sys.path.insert` at top so it can import root-level modules (`Model`, `Dataloader`) from subdirectory
- `compare_models.py` has a `MODELS` registry list — add new models by writing a `get_xxx_preds(train_loader, val_loader, device)` function and adding one line to the list; no plot code changes needed
- VGG16 feature dimension: 25088 (512 channels × 7×7 avgpool)
- KNN uses `predict_proba` (neighbor voting proportions) for ROC curves — coarse-grained but valid AUC
- Output: `baseline/roc_comparison.png`, `baseline/accuracy_bar.png`, `baseline/vgg_knn_confusion_matrix.png`
- Compare scripts output images to `baseline/` dir (not repo root)
## Model architecture reference
`Model.py` attribute names (for freezing / layer access):