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openfoodfacts
/
nutriscore-yolo

Object Detection
ONNX
food
Model card Files Community
Raphaël Bournhonesque commited on
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  1. F1_curve.png +0 -0
  2. PR_curve.png +0 -0
  3. P_curve.png +0 -0
  4. README.md +20 -0
  5. R_curve.png +0 -0
  6. args.yaml +106 -0
  7. confusion_matrix.png +0 -0
  8. confusion_matrix_normalized.png +0 -0
  9. labels.jpg +0 -0
  10. labels_correlogram.jpg +0 -0
  11. results.csv +101 -0
  12. results.png +0 -0
  13. train_batch0.jpg +0 -0
  14. train_batch1.jpg +0 -0
  15. train_batch2.jpg +0 -0
  16. train_batch2880.jpg +0 -0
  17. train_batch2881.jpg +0 -0
  18. train_batch2882.jpg +0 -0
  19. val_batch0_labels.jpg +0 -0
  20. val_batch0_pred.jpg +0 -0
  21. val_batch1_labels.jpg +0 -0
  22. val_batch1_pred.jpg +0 -0
  23. val_batch2_labels.jpg +0 -0
  24. val_batch2_pred.jpg +0 -0
  25. weights/best.onnx +3 -0
  26. weights/best.pt +3 -0
  27. weights/last.pt +3 -0
F1_curve.png ADDED
PR_curve.png ADDED
P_curve.png ADDED
README.md ADDED
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+ ---
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+ license: agpl-3.0
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+ datasets:
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+ - openfoodfacts/nutriscore-object-detection
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+ pipeline_tag: object-detection
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+ tags:
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+ - food
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+ ---
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+
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+ # Open Food Facts Nutriscore object detection model
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+
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+ This object detection model was trained on images from the Open Food Facts database to detect Nutri-score labels on food packaging.
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+
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+ It was trained on 100 epochs using Ultralytics YoloV8 with yolov8n as the backbone, with images resized to 640x640.
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+ This model is licensed under the AGPLv3 license.
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+
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+ ## Weights
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+
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+ Weights are available in the weights/ directory.
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+ An ONNX export of the model is available in weights/model.onnx.
R_curve.png ADDED
args.yaml ADDED
@@ -0,0 +1,106 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ task: detect
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+ mode: train
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+ model: yolov8n.pt
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+ data: data.yaml
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+ epochs: 100
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+ time: null
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+ patience: 100
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+ batch: 16
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+ imgsz: 640
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+ save: true
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+ save_period: -1
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+ cache: false
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+ device: null
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+ workers: 8
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+ project: null
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+ name: train
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+ exist_ok: false
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+ pretrained: true
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+ optimizer: auto
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+ verbose: true
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+ seed: 0
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+ deterministic: true
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+ single_cls: false
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+ rect: false
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+ cos_lr: false
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+ close_mosaic: 10
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+ resume: false
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+ amp: true
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+ fraction: 1.0
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+ profile: false
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+ freeze: null
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+ multi_scale: false
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+ overlap_mask: true
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+ mask_ratio: 4
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+ dropout: 0.0
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+ val: true
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+ split: val
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+ save_json: false
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+ save_hybrid: false
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+ conf: null
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+ iou: 0.7
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+ max_det: 300
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+ half: false
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+ dnn: false
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+ plots: true
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+ source: null
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+ vid_stride: 1
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+ stream_buffer: false
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+ visualize: false
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+ augment: false
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+ agnostic_nms: false
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+ classes: null
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+ retina_masks: false
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+ embed: null
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+ show: false
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+ save_frames: false
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+ save_txt: false
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+ save_conf: false
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+ save_crop: false
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+ show_labels: true
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+ show_conf: true
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+ show_boxes: true
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+ line_width: null
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+ format: torchscript
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+ keras: false
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+ optimize: false
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+ int8: false
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+ dynamic: false
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+ simplify: false
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+ opset: null
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+ workspace: 4
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+ nms: false
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+ lr0: 0.01
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+ lrf: 0.01
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+ momentum: 0.937
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+ weight_decay: 0.0005
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+ warmup_epochs: 3.0
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+ warmup_momentum: 0.8
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+ warmup_bias_lr: 0.1
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+ box: 7.5
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+ cls: 0.5
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+ dfl: 1.5
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+ pose: 12.0
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+ kobj: 1.0
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+ label_smoothing: 0.0
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+ nbs: 64
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+ hsv_h: 0.015
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+ hsv_s: 0.7
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+ hsv_v: 0.4
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+ degrees: 0.0
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+ translate: 0.1
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+ scale: 0.5
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+ shear: 0.0
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+ perspective: 0.0
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+ flipud: 0.0
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+ fliplr: 0.5
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+ bgr: 0.0
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+ mosaic: 1.0
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+ mixup: 0.0
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+ copy_paste: 0.0
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+ auto_augment: randaugment
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+ erasing: 0.4
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+ crop_fraction: 1.0
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+ cfg: null
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+ tracker: botsort.yaml
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+ save_dir: runs/detect/train
confusion_matrix.png ADDED
confusion_matrix_normalized.png ADDED
labels.jpg ADDED
labels_correlogram.jpg ADDED
results.csv ADDED
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