Update app.py

app.py

@@ -56,6 +56,8 @@ def detect_defect(img):
 
    
 def process_image(pilimg):
+    summary_str = "" # summary variable
+    
     # Perform classification first, then perform detection if Defective
     classification = classify_image(pilimg)
 
@@ -67,7 +69,8 @@ def process_image(pilimg):
         #font = ImageFont.truetype("arialbd.ttf", 30)  # Use arial.ttf for bold font
 
         draw.text((250, 10), "Good", fill="green", font=font)
-        gr.Info("No defect detected,GOOD!", duration=3)  
+        #gr.Info("No defect detected,GOOD!", duration=3)
+        summary_str = "No defect is detected, the cap is GOOD!"
 
     else:  # Defective
         detection_result = detect_defect(pilimg)
@@ -79,21 +82,26 @@ def process_image(pilimg):
         font = ImageFont.truetype(font_path, 30)
         #font = ImageFont.truetype("arialbd.ttf", 30)  # Use arial.ttf for bold font
 
-        draw.text((250, 10), "Defective", fill="red", font=font)
+        draw.text((330, 10), "Defective", fill="red", font=font)
         
         detections = detection_result[0].boxes.data  # Get detections
         if len(detections) > 0:
-            gr.Warning("Defect detected, BAD!", duration=3)
+            #gr.Warning("Defect detected, BAD!", duration=3)
+            summary_str = "Defect is detected, the cap is BAD"
         else:
-            gr.Warning("Classified as Defective but defect cannot be detected, ERROR!")
+            #gr.Warning("Classified as Defective but defect cannot be detected, ERROR!")
+            summary_str = "The cap is classifed as Defective but defect cannot be detected, ERROR!"
             
-    return out_pilimg
+    return out_pilimg, summary_str
 
-title = "Detect the status of the cap, DEFECTIVE or GOOD"
+title = "Detect the status of the cap: DEFECTIVE or GOOD"
 interface = gr.Interface(
                 fn=process_image,
                 inputs=gr.Image(type="pil", label="Input Image"),
-                outputs=gr.Image(type="pil", label="Classification result"),
+                outputs=[
+                    gr.Image(type="pil", label="Classification/Detection result"),
+                    gr.Textbox(label="Classification/Detection Summary"),
+                ],
                 title=title,
              )