Update app.py

app.py

@@ -1,11 +1,22 @@
 import gradio as gr
 import yolov7
+import subprocess
 import tempfile
-import cv2
-import numpy as np
+import time
 from pathlib import Path
+import uuid
+import cv2
+import gradio as gr
 
-def image_fn(image, model_path, image_size, conf_threshold, iou_threshold):
+
+    
+def image_fn(
+    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,
+):
     """
     YOLOv7 inference function
     Args:
@@ -17,44 +28,42 @@ def image_fn(image, model_path, image_size, conf_threshold, iou_threshold):
     Returns:
         Rendered image
     """
+
     model = yolov7.load(model_path, device="cpu", hf_model=True, trace=False)
     model.conf = conf_threshold
     model.iou = iou_threshold
     results = model([image], size=image_size)
-    
-    # Convert PIL image to NumPy array if necessary
-    if isinstance(results.render()[0], np.ndarray):
-        img = results.render()[0]
-    else:
-        img = np.array(results.render()[0])
-    
-    # Ensure the image array is writable
-    img.flags.writeable = True
-    
-    return img
+    return results.render()[0]
+  
+  
+        
 
-# Use gr instead of gr.inputs and gr.outputs
 image_interface = gr.Interface(
     fn=image_fn,
     inputs=[
-        gr.Image(type="pil", label="Input Image"),
-        gr.Dropdown(
-            choices=["Aalaa/Yolov7_Visual_Pollution_Detection"],
-            value="Aalaa/Yolov7_Visual_Pollution_Detection",
-            label="Model"
-        ),
-        gr.Slider(minimum=320, maximum=1280, value=640, step=32, label="Image Size"),
-        gr.Slider(minimum=0.0, maximum=1.0, value=0.25, step=0.05, label="Confidence Threshold"),
-        gr.Slider(minimum=0.0, maximum=1.0, value=0.45, step=0.05, label="IOU Threshold")
-    ],
-    outputs=gr.Image(type="numpy", label="Output Image"),
+    gr.inputs.Image(type="numpy", label="Input Image"),
+    gr.inputs.Dropdown(
+        choices=[
+            "Aalaa/Yolov7_Visual_Pollution_Detection",
+        ],
+        default="Aalaa/Yolov7_Visual_Pollution_Detection",
+        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="filepath", label="Output Image"),
+    
     examples=[['image1.jpg', 'Aalaa/Yolov7_Visual_Pollution_Detection', 640, 0.25, 0.45]],
     cache_examples=True,
-    theme='default'
+    theme='huggingface',
 )
 
+
+
 if __name__ == "__main__":
     gr.TabbedInterface(
         [image_interface],
         ["Run on Images"],
-    ).launch()
+    ).launch()