Update index.html

index.html

@@ -22,19 +22,57 @@
             <gradio-file name="app.py" entrypoint>
 import gradio as gr
 from transformers_js_py import pipeline
+from filters import convert
 
 pipe = await pipeline('object-detection', 'Xenova/detr-resnet-50')
 
-demo = gr.Interface.from_pipeline(pipe)
+async def fn(image):
+	result = await pipe(image)
+	return result
+              
+#demo = gr.Interface.from_pipeline(pipe)
 
+async def predict(image):
+  result = await pipe(image)
+  print(result)
+  result = convert(result)
+  print(result) 
+  return image, result
+
+demo = gr.Interface(
+  fn=predict,
+  inputs=gr.Image(type='pil'),
+  outputs=gr.AnnotatedImage(),
+)
+         
 demo.launch()
             </gradio-file>
 
             <gradio-file name="filters.py">
-from skimage.color import rgb2gray
+def convert(input_data):
+    # Initialize the output list
+    result_labels = []
+
+    # Iterate over each item in the input data
+    for item in input_data:
+        # Extract the label
+        label = item['label']
+        
+        # Extract the bounding box coordinates
+        xmin = item['box']['xmin']
+        ymin = item['box']['ymin']
+        xmax = item['box']['xmax']
+        ymax = item['box']['ymax']
+
+        # Convert coordinates into the required output format (list of coordinates)
+        coordinates = [xmin, ymin, xmax, ymax]
+
+        # Append the tuple of coordinates and label to the output list
+        result_labels.append((coordinates, label))
+
+    # Return the output list
+    return result_labels
 
-def as_gray(image):
-    return rgb2gray(image)
             </gradio-file>
 
             <gradio-file name="lion.jpg" url="https://raw.githubusercontent.com/gradio-app/gradio/main/gradio/test_data/lion.jpg" />