Update the labels in app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import torch
 from PIL import ImageDraw
+import pathlib
 
 # Model  
 model_path = 'model_torch.pt'
@@ -17,14 +18,17 @@ def detect_objects(image):
 
     detections = model(image)
 
+    probabilities = {}
+
     for detection in detections.xyxy[0]:
         
         x1, y1, x2, y2, p, category_id = detection
         x1, y1, x2, y2, category_id = int(x1), int(y1), int(x2), int(y2), int(category_id)
         draw.rectangle((x1, y1, x2, y2), outline=colors[category_id], width=4)
         draw.text((x1, y1), labels[category_id], colors[category_id])
+        probabilities[labels[category_id]] = float(p)
 
-    return image
+    return [image, probabilities]
 
 
 demo = gr.Blocks()#(css=css)
@@ -32,8 +36,6 @@ demo = gr.Blocks()#(css=css)
 title = '# 3D print failures detection App'
 description = 'App for detect errors in the 3D printing'
 
-urls = ["https://c8.alamy.com/comp/J2AB4K/the-new-york-stock-exchange-on-the-wall-street-in-new-york-J2AB4K.jpg"]
-
 with demo:
     gr.Markdown(title)
     gr.Markdown(description)
@@ -41,18 +43,20 @@ with demo:
     with gr.Tabs():
         with gr.TabItem('Image Upload'):
             with gr.Row():
-                img_input = gr.Image(type='pil')
-                img_output= gr.Image()
                 
-            #with gr.Row(): 
-            #    example_images = gr.Dataset(components=[img_input],
-            #                                samples=[[path.as_posix()]
-            #                                         for path in sorted(pathlib.Path('images').rglob('*.JPG'))])
+                with gr.Column():
+                    img_input = gr.Image(type='pil')
+                    examples_images2 = gr.Examples(examples = [[path.as_posix()] for path in sorted(pathlib.Path('images').rglob('*.jpg'))],
+                                               inputs=img_input)
+                    labels_bars = gr.Label(label = "Categories")
+                    print(labels_bars)
                 
+                with gr.Column():
+                    img_output= gr.Image()
+
             img_button = gr.Button('Detect')
         
-
-    img_button.click(detect_objects,inputs=img_input,outputs=img_output)
+    img_button.click(detect_objects,inputs=img_input,outputs=[img_output, labels_bars])
     
 
 if __name__ == "__main__":