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scripts/pt_example.py

@@ -10,7 +10,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 model = SamModel.from_pretrained("flaviagiammarino/medsam-vit-base").to(device)
 processor = SamProcessor.from_pretrained("flaviagiammarino/medsam-vit-base")
 
-img_url = "https://raw.githubusercontent.com/bowang-lab/MedSAM/main/assets/img_demo.png"
+img_url = "https://huggingface.co/flaviagiammarino/medsam-vit-base/resolve/main/scripts/input.png"
 raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB")
 input_boxes = [95., 255., 190., 350.]
 
@@ -42,4 +42,4 @@ show_mask(mask=probs[0] > 0.5, ax=ax[1], random_color=False)
 show_box(input_boxes, ax[1])
 ax[1].set_title("MedSAM Segmentation")
 ax[1].axis("off")
-plt.show()
+plt.show()

scripts/tf_example.py

@@ -8,7 +8,7 @@ import tensorflow as tf
 model = TFSamModel.from_pretrained("flaviagiammarino/medsam-vit-base")
 processor = SamProcessor.from_pretrained("flaviagiammarino/medsam-vit-base")
 
-img_url = "https://raw.githubusercontent.com/bowang-lab/MedSAM/main/assets/img_demo.png"
+img_url = "https://huggingface.co/flaviagiammarino/medsam-vit-base/resolve/main/scripts/input.png"
 raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB")
 input_boxes = [95., 255., 190., 350.]