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app.py

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+import sys
+import os
+import cv2
+import matplotlib
+import matplotlib.pyplot as plt
+import numpy as np
+import torch
+import torchvision
+import glob
+import gradio as gr
+from PIL import Image
+from segment_anything import SamAutomaticMaskGenerator, SamPredictor, sam_model_registry
+import logging
+from huggingface_hub import hf_hub_download
+
+token = os.environ['HUB_TOKEN']
+loc =hf_hub_download(repo_id="JunchuanYu/files_for_segmentRS", filename="utils.py",repo_type="dataset",local_dir='.',token=token)
+sys.path.append(loc)
+from utils import *
+
+with gr.Blocks(theme='gradio/soft') as demo:
+    gr.Markdown(title)
+    with gr.Accordion("Instructions For User 👉", open=False):
+        gr.Markdown(description)
+    x=gr.State(value=[])
+    y=gr.State(value=[])
+    label=gr.State(value=[])
+
+    with gr.Row():
+        with gr.Column():  
+            mode=gr.inputs.Radio(['Positive','Negative'], type="value",default='Positive',label='Types of sampling methods')
+        with gr.Column():
+                clear_bn=gr.Button("Clear Selection")
+                interseg_button = gr.Button("Interactive Segment",variant='primary')
+    with gr.Row():
+        input_img = gr.Image(label="Input")
+        gallery = gr.Image(label="Selected Sample Points")
+        
+    input_img.select(get_select_coords, [input_img, mode,x,y,label], [gallery,x,y,label])
+    
+    with gr.Row():
+        output_img = gr.Image(label="Result")           
+        mask_img = gr.Image(label="Mask")      
+    with gr.Row():
+        with gr.Column():
+            pred_iou_thresh = gr.Slider(minimum=0.8, maximum=1, value=0.90, step=0.01, interactive=True, label="Prediction Thresh")
+        with gr.Column():
+            points_per_side = gr.Slider(minimum=16, maximum=96, value=32, step=16, interactive=True, label="Points Per Side")
+    autoseg_button = gr.Button("Auto Segment",variant="primary")
+    emptyBtn = gr.Button("Restart",variant="secondary")
+
+    interseg_button.click(interactive_seg, inputs=[input_img,x,y,label], outputs=[output_img,mask_img])
+    autoseg_button.click(auto_seg, inputs=[input_img,pred_iou_thresh,points_per_side], outputs=[mask_img])
+
+    clear_bn.click(clear_point,outputs=[gallery,x,y,label],show_progress=True)
+    emptyBtn.click(reset_state,outputs=[input_img,gallery,output_img,mask_img,x,y,label],show_progress=True,)   
+    
+    example = gr.Examples(
+        examples=[[s,0.88,32] for s in glob.glob('./images/*')],
+        fn=auto_seg,
+        inputs=[input_img,pred_iou_thresh,points_per_side],
+        outputs=[output_img],
+        cache_examples=False,examples_per_page=5)
+    
+    gr.Markdown(descriptionend)
+if __name__ == "__main__":
+    demo.launch(debug=False,show_api=False)

requirements.txt

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+opencv-python
+matplotlib
+numpy
+torch
+torchvision
+https://files.pythonhosted.org/packages/f0/be/fd3e87763d13936186016eceee874c3ecc55a69213e8cc18e800e5fbc4b3/gradio-3.26.0-py3-none-any.whl
+git+https://github.com/facebookresearch/segment-anything.git