Image Segmentation
sam2
Safetensors
segmentation
medical-imaging
polyp-detection
gastrointestinal
colonoscopy
Eval Results (legacy)
Instructions to use usama10/sam2-kvasir-polyp-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sam2
How to use usama10/sam2-kvasir-polyp-segmentation with sam2:
# Use SAM2 with images import torch from sam2.sam2_image_predictor import SAM2ImagePredictor predictor = SAM2ImagePredictor.from_pretrained("usama10/sam2-kvasir-polyp-segmentation") with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16): predictor.set_image(<your_image>) masks, _, _ = predictor.predict(<input_prompts>)# Use SAM2 with videos import torch from sam2.sam2_video_predictor import SAM2VideoPredictor predictor = SAM2VideoPredictor.from_pretrained("usama10/sam2-kvasir-polyp-segmentation") with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16): state = predictor.init_state(<your_video>) # add new prompts and instantly get the output on the same frame frame_idx, object_ids, masks = predictor.add_new_points(state, <your_prompts>) # propagate the prompts to get masklets throughout the video for frame_idx, object_ids, masks in predictor.propagate_in_video(state): ... - Notebooks
- Google Colab
- Kaggle
File size: 1,200 Bytes
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"image_processor": {
"data_format": "channels_first",
"default_to_square": true,
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "Sam2ImageProcessorFast",
"image_std": [
0.229,
0.224,
0.225
],
"mask_size": {
"height": 256,
"width": 256
},
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 1024,
"width": 1024
}
},
"point_pad_value": -10,
"processor_class": "Sam2VideoProcessor",
"target_size": 1024,
"video_processor": {
"data_format": "channels_first",
"default_to_square": true,
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_std": [
0.229,
0.224,
0.225
],
"resample": 2,
"rescale_factor": 0.00392156862745098,
"return_metadata": false,
"size": {
"height": 1024,
"width": 1024
},
"video_processor_type": "Sam2VideoVideoProcessor"
}
}
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