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--- |
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tags: |
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- object-detection |
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- rf-detr |
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- package-segmentation |
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- computer-vision |
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library_name: rfdetr |
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license: apache-2.0 |
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--- |
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# RF-DETR Package Detection Model |
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This model is a fine-tuned **RF-DETR Medium** model for package/box detection, trained on a custom dataset. |
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## Model Description |
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- **Model Type:** RF-DETR (Real-time DETR for object detection) |
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- **Base Model:** RF-DETR Medium |
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- **Task:** Object Detection (Package/Box Segmentation) |
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- **Training Data:** Custom dataset |
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- **Classes:** 2 class(es) |
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## Training Details |
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- **Epochs:** N/A |
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- **Batch Size:** 16 |
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- **Learning Rate:** 5e-05 |
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- **Input Resolution:** 576x576 |
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## Performance |
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Training metrics available in the model repository. |
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## Usage |
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### Installation |
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```bash |
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pip install rfdetr torch torchvision |
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``` |
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### Loading the Model |
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```python |
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import torch |
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from rfdetr import RFDETRMedium |
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from PIL import Image |
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# Load model |
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model = RFDETRMedium() |
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checkpoint = torch.load("checkpoint_best_total.pth", map_location='cpu') |
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model.model.load_state_dict(checkpoint['model']) |
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model.model.eval() |
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# Run inference |
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image = Image.open("path/to/image.jpg") |
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results = model.predict(image) |
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``` |
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### API Usage (with Inference Endpoints) |
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Once deployed as an Inference Endpoint: |
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```python |
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import requests |
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from PIL import Image |
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import io |
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API_URL = "https://api-inference.huggingface.co/models/YOUR_USERNAME/rf-detr-box-segmentation" |
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headers = {"Authorization": "Bearer YOUR_HF_TOKEN"} |
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# Send image |
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with open("image.jpg", "rb") as f: |
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data = f.read() |
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response = requests.post(API_URL, headers=headers, data=data) |
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results = response.json() |
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``` |
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## Model Details |
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- **Developed by:** Your Name |
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- **Model date:** 1762288019.2803671 |
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- **Framework:** PyTorch |
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- **License:** Apache 2.0 |
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## Citation |
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```bibtex |
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@software{rfdetr2024, |
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title = {RF-DETR: Real-time DETR}, |
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author = {Roboflow}, |
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year = {2024}, |
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url = {https://github.com/roboflow/rf-detr} |
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} |
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``` |
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## Limitations |
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This model is trained on a specific package detection dataset and may not generalize to all object detection tasks. |
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