Price Tag Detection

--- base_model: yolo11x.pt datasets: - openfoodfacts/price-tag-detection library_name: ultralytics license: agpl-3.0 pipeline_tag: object-detection tags: - price - price-tag - food - supermarket - open-prices --- # Open Prices - Price tag detection model [Wandb tracking run](https://wandb.ai/raphaeloff/price-tag-detection/runs/yolo11x-e-200-i-960_20260227_102910) This object detection model was trained on images from the Open Prices database to detect price tags of products in shops. It was trained on 200 epochs using Ultralytics library, using yolov11x version, with images resized to 960x960. This model is licensed under the AGPLv3 license. ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - **Developed by:** Open Food Facts - **Model type:** object detection - **License:** agpl-3.0 - **Finetuned from model:** yolo11x.pt ## Training Details ### Training Data The model was fine-tuned using the following dataset: [openfoodfacts/price-tag-detection](https://huggingface.co/datasets/openfoodfacts/price-tag-detection) (revision: `v1.2`). ### Training Procedure Dependency versions: - ultralytics: 8.4.14 - pytorch: 2.9.0+cu128 #### Training Hyperparameters - **Epochs:** 200 - **Batch size:** 16 - **Image size:** 960 ## Evaluation The following evaluation metrics were obtained after training the model: - **metrics/precision(B):** 0.9405504116589396 - **metrics/recall(B):** 0.8999179655455292 - **metrics/mAP50(B):** 0.9490994303327694 - **metrics/mAP50-95(B):** 0.8022528188009798 - **fitness:** 0.8022528188009798 ### Evaluation on exported models The model was also evaluated after exporting to ONNX and TensorRT formats. The following metrics were obtained: #### ONNX export - **metrics/precision(B):** 0.9393607953718663 - **metrics/recall(B):** 0.9048400328137818 - **metrics/mAP50(B):** 0.9485645846101123 - **metrics/mAP50-95(B):** 0.8000803959473284 - **fitness:** 0.8000803959473284 ## Files Most files stored on the repo are standard files created during training with the Ultralytics YOLO library. What was added: - an ONNX export of the trained model (best model), stored in `weights/model.onnx`. - a Parquet file containing predictions on the full dataset, stored in `predictions.parquet`. - metrics JSON files for each exported model format, stored in `metrics_*.json`: - `metrics.json`...

Source context: 546 downloads · 7 likes · Pipeline object-detection · Library ultralytics · Repo openfoodfacts/price-tag-detection

Source context: 752 downloads · 6 likes · Pipeline object-detection · Library ultralytics · Repo openfoodfacts/price-tag-detection