Update app.py

app.py

@@ -11,12 +11,7 @@ yolov7_custom_weights = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
 
 model = torch.hub.load('Owaiskhan9654/yolov7-1:main',model='custom', path_or_model=yolov7_custom_weights, force_reload=True)  # Github repository https://github.com/Owaiskhan9654
 
-def object_detection(
-    image: gr.inputs.Image = None,
-    model_path: gr.inputs.Dropdown = None,
-    image_size: gr.inputs.Slider = 640,
-    conf_threshold: gr.inputs.Slider = 0.25,
-    iou_threshold: gr.inputs.Slider = 0.45,):
+def object_detection(image: gr.inputs.Image = None):
   
 
     results = model(image) 
@@ -35,14 +30,13 @@ title = "Yolov7 Custom"
 
 # image = gr.inputs.Image(shape=(640, 640), image_mode="RGB", source="upload", label="Upload Image", optional=False)
 
-inputs = [
-    gr.inputs.Image(shape=(640, 640), image_mode="RGB", source="upload", label="Upload Image", optional=False),
-    gr.inputs.Dropdown(["best.pt",], 
-                       default="best.pt", label="Model"),
-    gr.inputs.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size"),
-    gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"),
-    gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold"),
-]
+inputs = gr.inputs.Image(shape=(640, 640), image_mode="RGB", source="upload", label="Upload Image", optional=False)
+#     gr.inputs.Dropdown(["best.pt",], 
+#                        default="best.pt", label="Model"),
+#     gr.inputs.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size"),
+#     gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"),
+#     gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold"),
+# ]
 outputs = gr.outputs.Image(type="pil", label="Output Image")
 outputs_cls = gr.Label(label= "Categories Detected Proportion Statistics" )