Create app.py

app.py

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+# 1. Import all the libraries
+import gradio as gr
+import cv2
+import mediapipe as mp
+import numpy as np
+import math
+import os # Import os to check for file
+
+# --- This dictionary now points to YOUR uploaded presets ---
+PRELOADED_MODELS = {
+    "Preset 1": "preset_1.stl",
+    "Preset 2": "preset_2.stl",
+    "Preset 3": "preset_3.stl"
+}
+
+# 4. Set up our MediaPipe objects
+mp_drawing = mp.solutions.drawing_utils
+mp_hands = mp.solutions.hands
+
+# We are detecting ONE hand
+hands = mp_hands.Hands(
+    max_num_hands=1,
+    min_detection_confidence=0.7,
+    min_tracking_confidence=0.5
+)
+
+# 5. --- GESTURE RECOGNIZER CLASS (Same as before) ---
+class GestureRecognizer:
+    def __init__(self):
+        self.PINCH_THRESHOLD = 0.08
+    
+    def _calculate_distance(self, lm1, lm2):
+        return math.sqrt((lm1.x - lm2.x)**2 + (lm1.y - lm2.y)**2)
+
+    def recognize(self, hand_landmarks):
+        landmarks = hand_landmarks.landmark
+        
+        wrist_pos = (landmarks[mp_hands.HandLandmark.WRIST].x, landmarks[mp_hands.HandLandmark.WRIST].y)
+        
+        # 1. Check for "PEACE SIGN"
+        index_extended = landmarks[mp_hands.HandLandmark.INDEX_FINGER_TIP].y < landmarks[mp_hands.HandLandmark.INDEX_FINGER_PIP].y
+        middle_extended = landmarks[mp_hands.HandLandmark.MIDDLE_FINGER_TIP].y < landmarks[mp_hands.HandLandmark.MIDDLE_FINGER_PIP].y
+        ring_curled = landmarks[mp_hands.HandLandmark.RING_FINGER_TIP].y > landmarks[mp_hands.HandLandmark.RING_FINGER_PIP].y
+        pinky_curled = landmarks[mp_hands.HandLandmark.PINKY_TIP].y > landmarks[mp_hands.HandLandmark.PINKY_PIP].y
+        
+        if index_extended and middle_extended and ring_curled and pinky_curled:
+            return "**PEACE**", wrist_pos
+            
+        # 2. Check for "FIST"
+        index_curled = landmarks[mp_hands.HandLandmark.INDEX_FINGER_TIP].y > landmarks[mp_hands.HandLandmark.INDEX_FINGER_PIP].y
+        middle_curled = landmarks[mp_hands.HandLandmark.MIDDLE_FINGER_TIP].y > landmarks[mp_hands.HandLandmark.MIDDLE_FINGER_PIP].y
+        ring_curled = landmarks[mp_hands.HandLandmark.RING_FINGER_TIP].y > landmarks[mp_hands.HandLandmark.RING_FINGER_PIP].y
+
+        if index_curled and middle_curled and ring_curled:
+            return "**FIST**", wrist_pos # Return wrist position
+
+        # 3. Check for "PINCH"
+        thumb_tip = landmarks[mp_hands.HandLandmark.THUMB_TIP]
+        index_tip = landmarks[mp_hands.HandLandmark.INDEX_FINGER_TIP]
+        pinch_distance = self._calculate_distance(thumb_tip, index_tip)
+        
+        if pinch_distance < self.PINCH_THRESHOLD:
+            return "**PINCH**", wrist_pos
+
+        # 4. If no other gesture, it's "OPEN"
+        return "**OPEN**", None
+
+# 6. --- Create an instance of our recognizer ---
+recognizer = GestureRecognizer()
+
+# 7. --- GESTURE PROCESSING FUNCTION (OPTIMIZED) ---
+
+DEFAULT_CAMERA = (0, 90, 150) 
+ROTATION_SENSITIVITY = 360
+ZOOM_SENSITIVITY = 75 # Your new faster zoom
+
+def process_image(webcam_frame, camera_state, prev_hand_pos_state):
+    
+    gesture_text = "No hand detected"
+    new_camera_state = camera_state
+    new_prev_hand_pos = None 
+    
+    (old_azimuth, old_polar, old_zoom) = camera_state
+    
+    if webcam_frame is None:
+        return "Waiting...", DEFAULT_CAMERA, None, gr.update(camera_position=DEFAULT_CAMERA)
+
+    # --- OPTIMIZATION 1: Pass by reference, don't copy ---
+    image = webcam_frame 
+    image.flags.writeable = False
+    results = hands.process(image)
+    # No need to set writeable=True, we aren't drawing
+    
+    if results.multi_hand_landmarks:
+        hand_landmarks = results.multi_hand_landmarks[0]
+        
+        current_gesture, current_hand_pos = recognizer.recognize(hand_landmarks)
+        gesture_text = current_gesture.replace("**", "") 
+        
+        if current_gesture == "**PEACE**":
+            new_camera_state = DEFAULT_CAMERA
+            gesture_text = "Resetting view!"
+        
+        elif current_hand_pos and prev_hand_pos_state:
+            delta_x = current_hand_pos[0] - prev_hand_pos_state[0]
+            delta_y = current_hand_pos[1] - prev_hand_pos_state[1]
+
+            if current_gesture == "**PINCH**":
+                new_azimuth = old_azimuth + (delta_x * ROTATION_SENSITIVITY)
+                new_polar = old_polar - (delta_y * ROTATION_SENSITIVITY) 
+                new_camera_state = (new_azimuth, new_polar, old_zoom)
+                gesture_text = "Rotating..."
+
+            elif current_gesture == "**FIST**":
+                new_zoom = old_zoom + (delta_x * ZOOM_SENSITIVITY) 
+                new_zoom = max(0.5, min(new_zoom, 400.0))
+                new_camera_state = (old_azimuth, old_polar, new_zoom)
+                gesture_text = "Zooming..."
+        
+        if current_hand_pos:
+            new_prev_hand_pos = current_hand_pos
+        
+        # --- OPTIMIZATION 2: Removed mp_drawing.draw_landmarks() ---
+    
+    else:
+        new_prev_hand_pos = None
+
+    # --- FIX 2: Return 4 values, removing the image ---
+    return gesture_text, new_camera_state, new_prev_hand_pos, gr.update(camera_position=new_camera_state)
+
+# 8. --- HELPER FUNCTIONS ---
+
+def load_preloaded_model(model_name):
+    file_path = PRELOADED_MODELS[model_name]
+    return gr.update(value=file_path), gr.update(value=DEFAULT_CAMERA)
+
+def load_uploaded_model(temp_file):
+    return gr.update(value=temp_file.name), gr.update(value=DEFAULT_CAMERA)
+
+
+# 9. --- Create and launch the Gradio Interface ---
+with gr.Blocks(theme=gr.themes.Glass()) as demo:
+    
+    camera_state = gr.State(value=DEFAULT_CAMERA)
+    prev_hand_pos_state = gr.State(value=None)
+    
+    with gr.Row():
+        gr.Markdown("# 🖐️ Gesture-Controlled 3D Viewer")
+        
+    with gr.Row():
+        # --- UI Column for controls ---
+        with gr.Column(scale=1):
+            gr.Markdown("### 1. Select a Model")
+            with gr.Tabs():
+                with gr.Tab("Your Presets"):
+                    radio_picker = gr.Radio(
+                        choices=list(PRELOADED_MODELS.keys()), 
+                        label="Select your preset model",
+                        value="Preset 1"
+                    )
+                with gr.Tab("Upload"):
+                    file_uploader = gr.File(
+                        label="Upload .stl, .obj, .glb, or .3mf",
+                        file_types=['.stl', '.obj', '.glb', '.gltf', '.3mf']
+                    )
+            
+            gr.Markdown("### 2. Control with Webcam")
+            webcam_input = gr.Image(sources=["webcam"], streaming=True, label="Webcam Feed")
+            
+            gr.Markdown("### 3. Gesture Status")
+            text_output = gr.Text(label="Status")
+            
+        # --- MAIN COLUMN for 3D viewer ---
+        with gr.Column(scale=3):
+            default_model_path = PRELOADED_MODELS.get("Preset 1", None)
+            # This check is now for the deployment environment
+            if not os.path.exists(default_model_path):
+                print(f"Warning: Default preset '{default_model_path}' not found.")
+                default_model_path = None
+            
+            model_3d = gr.Model3D(
+                value=default_model_path,
+                label=None,
+                camera_position=DEFAULT_CAMERA,
+                interactive=False
+            )
+            
+            gr.Markdown(
+                """
+                <div style="width: 100%; text-align: center;">
+                <b>Gesture Controls:</b> ✌️ <b>Peace Sign:</b> Reset/Home | 👌 <b>Pinch & Move:</b> Rotate | ✊ <b>Fist & Move Left/Right:</b> Zoom
+                </div>
+                """
+            )
+            
+            # --- OPTIMIZATION 3: Removed webcam_output component ---
+            
+    # --- 10. WIRE UP THE NEW CONTROLS ---
+    
+    # 1. Wire up the Radio buttons
+    radio_picker.change(
+        fn=load_preloaded_model, 
+        inputs=radio_picker, 
+        outputs=[model_3d, camera_state]
+    )
+    
+    # 2. Wire up the File uploader
+    file_uploader.upload(
+        fn=load_uploaded_model, 
+        inputs=file_uploader, 
+        outputs=[model_3d, camera_state]
+    )
+    
+    # 3. Wire up the webcam gesture controls
+    webcam_input.stream(
+        fn=process_image,
+        inputs=[
+            webcam_input,
+            camera_state,
+            prev_hand_pos_state
+        ],
+        outputs=[
+            text_output,
+            camera_state,
+            prev_hand_pos_state,
+            model_3d
+        ]
+    )
+
+# --- THIS IS THE FINAL, NEW LAUNCH COMMAND ---
+# This makes your app public but requires a password to access.
+# You can change "guest" to any username you want.
+demo.launch(auth=("guest", "Its_zion_18"))