Update app.py

app.py

@@ -5,18 +5,22 @@ import traceback
 import numpy as np
 import gradio as gr
 from itertools import chain
+from huggingface_hub import hf_hub_download
 from segment_anything import SamPredictor, sam_model_registry
 
 
-sam_checkpoint = "sam_vit_h_4b8939.pth"
+hf_hub_download(repo_id="vmoras/sam_api", filename="sam_vit_h.pth")
+
+
+sam_checkpoint = "sam_vit_h.pth"
 model_type = "vit_h"
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
 
 def set_predictor(image):
     """
     Creates a Sam predictor object based on a given image and model.
     """
-    device = 'cuda' if torch.cuda.is_available() else 'cpu'
     sam = sam_model_registry[model_type](checkpoint=sam_checkpoint)
     sam.to(device=device)
 
@@ -84,19 +88,18 @@ with gr.Blocks() as demo:
     4. Click on the image where the lower right corner of the bbox should be
     5. Check the coordinates using the 'bbox' box
     6. Click on 'Send bounding box'
-    7. On the right side you will see the binary mask*
-    8. on the lower side you will see the points that made up the polygon*
+    7. On the right side you will see the binary mask ·
+    8. on the lower side you will see the points that made up the polygon ·
     9. Click on 'Clear bbox' to send another bounding box and repeat the steps from the thrid point
     10. Repeat steps 3 to 9 until all the segments for this image are done
     11. Click on the right corner of the image to remove it and repeat all the steps with the next 
     image
 
-    * If the binary mask is all black and the polygon is an empty list, it means the program did 
+    · If the binary mask is all black and the polygon is an empty list, it means the program did 
     not find any segment in the bbox. Make the bbox a little big bigger if that happens.
     """)
 
 
-
     image = gr.State()
     embedding = gr.State()
     bbox = gr.State([[0, 0], [0, 0]])