Update requirements

app.py

@@ -92,8 +92,9 @@ def post_process(annotations, image, mask_random_color=True, bbox=None, points=N
 
 # post_process(results[0].masks, Image.open("../data/cake.png"))
 
-def predict(inp):
-    results = model(inp, device='cpu', retina_masks=True, iou=0.7, conf=0.25, imgsz=720)
+def predict(inp, imgsz):
+    imgsz = int(imgsz)  # 确保 imgsz 是整数
+    results = model(inp, device='cpu', retina_masks=True, iou=0.7, conf=0.25, imgsz=imgsz)
     results = format_results(results[0], 100)
     results.sort(key=lambda x: x['area'], reverse=True)
     pil_image = post_process(annotations=results, image=inp)
@@ -105,9 +106,10 @@ def predict(inp):
 # post_process(annotations=results, image_path=inp)
 
 demo = gr.Interface(fn=predict,
-                    inputs=gr.inputs.Image(type='pil'),
+                    inputs=[gr.inputs.Image(type='pil'), gr.inputs.Dropdown(choices=[800, 960, 1024])],
                     outputs=['plot'],
-                     examples=[["assets/sa_8776.jpg"],],
+                     examples=[["assets/sa_8776.jpg", 1024],
+                               ["assets/sa_1309.jpg", 1024]],
                     # examples=[["assets/sa_192.jpg"], ["assets/sa_414.jpg"],
                     #           ["assets/sa_561.jpg"], ["assets/sa_862.jpg"],
                     #           ["assets/sa_1309.jpg"], ["assets/sa_8776.jpg"],