Update app.py

app.py

@@ -46,12 +46,78 @@ def log_emotion(batch_no, emotion, confidence, face_path, annotated_path):
         writer = csv.writer(f)
         writer.writerow([timestamp, batch_no, emotion, confidence, str(face_path), str(annotated_path)])
 
+def validate_batch_number(batch_no):
+    """Validate that batch number contains only digits"""
+    if not batch_no.strip():
+        return False, "Batch number cannot be empty"
+    if not batch_no.isdigit():
+        return False, "Batch number must contain only numbers"
+    return True, ""
+
+def toggle_webcam_flow(batch_no):
+    """Control visibility of components based on flow"""
+    if batch_no.strip():
+        # Validate batch number
+        is_valid, validation_msg = validate_batch_number(batch_no)
+        if not is_valid:
+            return {
+                batch_no_input: gr.Textbox(visible=True, value=""),
+                webcam: gr.Image(visible=False),
+                message: gr.Textbox(value=validation_msg, visible=True),
+                batch_no_state: ""
+            }
+        
+        # Valid batch number - hide input, show webcam
+        return {
+            batch_no_input: gr.Textbox(visible=False),
+            webcam: gr.Image(visible=True),
+            message: gr.Textbox(visible=False),
+            batch_no_state: batch_no
+        }
+    else:
+        # No batch number - show input, hide webcam
+        return {
+            batch_no_input: gr.Textbox(visible=True),
+            webcam: gr.Image(visible=False),
+            message: gr.Textbox(visible=False),
+            batch_no_state: ""
+        }
+
 def predict_emotion(batch_no: str, image):
     if not batch_no.strip():
-        return None, None, "Please enter a batch number first", gr.Image(visible=False), gr.Textbox(visible=False)
+        return {
+            result_img: None,
+            result_text: None,
+            message: gr.Textbox(value="Please enter a batch number first", visible=True),
+            result_img_comp: gr.Image(visible=False),
+            result_text_comp: gr.Textbox(visible=False),
+            batch_no_input: gr.Textbox(visible=True),
+            webcam: gr.Image(visible=False)
+        }
+    
+    # Validate batch number format
+    is_valid, validation_msg = validate_batch_number(batch_no)
+    if not is_valid:
+        return {
+            result_img: None,
+            result_text: None,
+            message: gr.Textbox(value=validation_msg, visible=True),
+            result_img_comp: gr.Image(visible=False),
+            result_text_comp: gr.Textbox(visible=False),
+            batch_no_input: gr.Textbox(visible=True),
+            webcam: gr.Image(visible=False)
+        }
     
     if image is None:
-        return None, None, "Please capture your face first", gr.Image(visible=False), gr.Textbox(visible=False)
+        return {
+            result_img: None,
+            result_text: None,
+            message: gr.Textbox(value="Please capture your face first", visible=True),
+            result_img_comp: gr.Image(visible=False),
+            result_text_comp: gr.Textbox(visible=False),
+            batch_no_input: gr.Textbox(visible=False),
+            webcam: gr.Image(visible=True)
+        }
     
     try:
         # Convert PIL Image to OpenCV format
@@ -75,7 +141,15 @@ def predict_emotion(batch_no: str, image):
                 continue
 
         if not results:
-            return None, None, "No face detected. Please try again.", gr.Image(visible=False), gr.Textbox(visible=False)
+            return {
+                result_img: None,
+                result_text: None,
+                message: gr.Textbox(value="No face detected. Please try again.", visible=True),
+                result_img_comp: gr.Image(visible=False),
+                result_text_comp: gr.Textbox(visible=False),
+                batch_no_input: gr.Textbox(visible=True),
+                webcam: gr.Image(visible=False)
+            }
 
         # Process the first face found
         result = results[0] if isinstance(results, list) else results
@@ -108,15 +182,27 @@ def predict_emotion(batch_no: str, image):
         
         # Convert back to PIL format for display
         output_img = Image.fromarray(cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB))
-        return output_img, f"Batch {batch_no}: {emotion.title()} ({confidence:.1f}%)", "", gr.Image(visible=True), gr.Textbox(visible=True)
+        
+        return {
+            result_img: output_img,
+            result_text: f"Batch {batch_no}: {emotion.title()} ({confidence:.1f}%)",
+            message: gr.Textbox(visible=False),
+            result_img_comp: gr.Image(visible=True),
+            result_text_comp: gr.Textbox(visible=True),
+            batch_no_input: gr.Textbox(visible=True, value=""),
+            webcam: gr.Image(visible=False)
+        }
     
     except Exception as e:
-        return None, None, f"Error processing image: {str(e)}", gr.Image(visible=False), gr.Textbox(visible=False)
-
-def toggle_webcam(batch_no):
-    if batch_no.strip():
-        return gr.Image(visible=True), gr.Image(visible=False), gr.Textbox(visible=False), ""
-    return gr.Image(visible=False), gr.Image(visible=False), gr.Textbox(visible=False), "Please enter a batch number"
+        return {
+            result_img: None,
+            result_text: None,
+            message: gr.Textbox(value=f"Error processing image: {str(e)}", visible=True),
+            result_img_comp: gr.Image(visible=False),
+            result_text_comp: gr.Textbox(visible=False),
+            batch_no_input: gr.Textbox(visible=True, value=""),
+            webcam: gr.Image(visible=False)
+        }
 
 def get_image_gallery(emotion, image_type):
     """Get image gallery for selected emotion and type"""
@@ -362,42 +448,63 @@ with gr.Blocks(title="Emotion Capture", css="""
     
     gr.Markdown("""
     # Emotion Capture Interface
-    1. Enter your batch number
-    2. Capture your face (will appear after step 1)
-    3. View your emotion analysis results (will appear after step 2)
+    1. Enter your batch number (numbers only)
+    2. Capture your face (webcam will appear)
+    3. View your emotion analysis results
+    4. Interface will reset automatically for next user
     """)
     
-    with gr.Row():
-        batch_no = gr.Textbox(label="Batch Number", placeholder="Enter your ID or batch number")
-        message = gr.Textbox(label="", visible=False, interactive=False, elem_classes="message")
+    # Add a state to store batch number between callbacks
+    batch_no_state = gr.State("")
     
-    # Components that will be shown/hidden
     with gr.Row():
-        webcam = gr.Image(
-            sources=["webcam"],
-            type="pil",
-            label="Face Capture",
-            interactive=True,
-            mirror_webcam=True,
-            visible=False
+        batch_no_input = gr.Textbox(
+            label="Batch Number", 
+            placeholder="Enter numbers only",
+            visible=True
         )
+        message = gr.Textbox(label="", visible=False, interactive=False, elem_classes="message")
+    
+    # Webcam component starts hidden
+    webcam = gr.Image(
+        sources=["webcam"],
+        type="pil",
+        label="Face Capture",
+        interactive=True,
+        mirror_webcam=True,
+        visible=False
+    )
+    
+    # Results components
     with gr.Row():
         result_img = gr.Image(label="Analysis Result", interactive=False, visible=False)
     with gr.Row():
         result_text = gr.Textbox(label="Emotion Result", interactive=False, visible=False)
     
-    # Show webcam when batch number is entered
-    batch_no.change(
-        toggle_webcam,
-        inputs=batch_no,
-        outputs=[webcam, result_img, result_text, message]
+    # Track visibility separately for easier management
+    result_img_comp = gr.Image(visible=False)
+    result_text_comp = gr.Textbox(visible=False)
+    
+    # Show webcam when valid batch number is entered
+    batch_no_input.change(
+        toggle_webcam_flow,
+        inputs=batch_no_input,
+        outputs=[batch_no_input, webcam, message, batch_no_state]
     )
     
     # Process when webcam captures an image
     webcam.change(
         predict_emotion,
-        inputs=[batch_no, webcam],
-        outputs=[result_img, result_text, message, result_img, result_text]
+        inputs=[batch_no_state, webcam],
+        outputs=[
+            result_img, 
+            result_text, 
+            message, 
+            result_img_comp,
+            result_text_comp,
+            batch_no_input,
+            webcam
+        ]
     )
 
 # Data Management Interface