(I'm currently updating this repo)
In this project, we applied yolov5 to classify 4 type of bottles:
- bottle_cap
- bottle_uncap
- fallen_bottle
- flip_bottle
- Table of Contents
- Install Requirements
- Data Format
- Download Yolov7 Weights
- Evaluation
- Training
- Result
- Citation
- Acknowledgement
Expand
| Package | Version |
|---|---|
| absl-py | 1.4.0 |
| albumentations | 1.3.0 |
| appdirs | 1.4.4 |
| attrs | 22.2.0 |
| backcall | 0.2.0 |
| cachetools | 5.3.0 |
| certifi | 2022.12.7 |
| chardet | 4.0.0 |
| charset-normalizer | 3.1.0 |
| clearml | 1.10.3 |
| click | 8.1.3 |
| clip | 0.2.0 |
| cycler | 0.11.0 |
| decorator | 5.1.1 |
| docker-pycreds | 0.4.0 |
| fonttools | 4.38.0 |
| furl | 2.1.3 |
| gitdb | 4.0.10 |
| GitPython | 3.1.31 |
| google-auth | 2.17.2 |
| google-auth-oauthlib | 0.4.6 |
| grpcio | 1.53.0 |
| idna | 3.4 |
| imageio | 2.27.0 |
| imgaug | 0.4.0 |
| importlib-metadata | 6.3.0 |
| importlib-resources | 5.12.0 |
| ipython | 7.34.0 |
| jedi | 0.18.2 |
| joblib | 1.2.0 |
| jsonschema | 4.17.3 |
| kiwisolver | 1.4.4 |
| Markdown | 3.4.3 |
| MarkupSafe | 2.1.2 |
| matplotlib | 3.5.3 |
| matplotlib-inline | 0.1.6 |
| networkx | 2.6.3 |
| numpy | 1.21.6 |
| nvidia-cublas-cu11 | 11.10.3.66 |
| nvidia-cuda-nvrtc-cu11 | 11.7.99 |
| nvidia-cuda-runtime-cu11 | 11.7.99 |
| nvidia-cudnn-cu11 | 8.5.0.96 |
| oauthlib | 3.2.2 |
| opencv-python | 4.7.0.72 |
| opencv-python-headless | 4.7.0.72 |
| orderedmultidict | 1.0.1 |
| packaging | 23.0 |
| pandas | 1.3.5 |
| parso | 0.8.3 |
| pathlib2 | 2.3.7.post1 |
| pathtools | 0.1.2 |
| pexpect | 4.8.0 |
| pickleshare | 0.7.5 |
| Pillow | 9.5.0 |
| pip | 23.0.1 |
| pkgutil_resolve_name | 1.3.10 |
| prompt-toolkit | 3.0.38 |
| protobuf | 3.20.1 |
| psutil | 5.9.4 |
| ptyprocess | 0.7.0 |
| pyasn1 | 0.4.8 |
| pyasn1-modules | 0.2.8 |
| pycocotools | 2.0.6 |
| Pygments | 2.14.0 |
| PyJWT | 2.4.0 |
| pyparsing | 3.0.9 |
| pyrsistent | 0.19.3 |
| python-dateutil | 2.8.2 |
| python-dotenv | 0.21.1 |
| pytz | 2023.3 |
| PyWavelets | 1.3.0 |
| PyYAML | 6.0 |
| qudida | 0.0.4 |
| requests | 2.28.2 |
| requests-oauthlib | 1.3.1 |
| requests-toolbelt | 0.10.1 |
| roboflow | 1.0.3 |
| rsa | 4.9 |
| scikit-image | 0.19.3 |
| scikit-learn | 1.0.2 |
| scipy | 1.7.3 |
| seaborn | 0.12.2 |
| sentry-sdk | 1.19.1 |
| setproctitle | 1.3.2 |
| setuptools | 47.1.0 |
| shapely | 2.0.1 |
| six | 1.16.0 |
| smmap | 5.0.0 |
| tensorboard | 2.11.2 |
| tensorboard-data-server | 0.6.1 |
| tensorboard-plugin-wit | 1.8.1 |
| thop | 0.1.1.post2209072238 |
| threadpoolctl | 3.1.0 |
| tifffile | 2021.11.2 |
| torch | 1.10.1+cu102 |
| torch-tb-profiler | 0.4.1 |
| torchaudio | 0.10.1+cu102 |
| torchvision | 0.11.2+cu102 |
| tqdm | 4.65.0 |
| traitlets | 5.9.0 |
| typing_extensions | 4.5.0 |
| ultralytics | 8.0.110 |
| urllib3 | 1.26.15 |
| wandb | 0.14.2 |
| wcwidth | 0.2.6 |
| Werkzeug | 2.2.3 |
| wget | 3.2 |
| wheel | 0.40.0 |
| zipp | 3.15.0 |
Expand
bottle_classification
|
|____command
|
|_____data_bottle_detection
| |
| |________test
| | |______.png #image file
| | |_______.png.json #Json file
| |
| |________train
| | |______.png #image file
| | |_______.png.json #Json file
| |
| |_____train_data
| | |_________images
| | |
| | |_________labels
| |
| |
| |
| |
| |______seg
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |______predict_crop_data # images will be saved when run inference_blisters.py
| |
| |______predict_test_data # images will be saved when run inference_blisters.py
|
|______seg
|
|
|
|
|_____data
| |
| |_______hyps
| | |_______coco.yaml
| | |_______hyp.scratch-high.yaml
| | |_______hyp.scratch-low.yaml
| | |_______hyp.scratch-med.yaml
| |
| |________scripts
| |________coco.yaml
|
|_______models
|
|_______runs
|
|_______segment
|
|_______utils
Start training
# Move to seg directory
cd ~/bottle_classification/seg
python3 segment/train.py --weights=/home/tonyhuy/TOMO/Instance_segmentation/yolov7_mask/seg/yolov5s-seg.pt --data=/home/tonyhuy/bottle_classification/seg/data/coco.yaml --hyp=/home/tonyhuy/bottle_classification/seg/data/hyps/hyp.scratch-med.yaml --epochs=300 --device=5