Update app.py

app.py

@@ -6,17 +6,6 @@ from typing import Optional, Tuple
 from datetime import datetime
 from PIL import Image
 
-# Попытка импортировать st_canvas; если не установлен, интерактивный режим будет отключён.
-try:
-    from streamlit_drawable_canvas import st_canvas
-    canvas_available = True
-except ImportError:
-    canvas_available = False
-    st.warning(
-        "Интерактивное редактирование отключено, так как модуль streamlit-drawable-canvas не установлен. "
-        "Для его использования добавьте 'streamlit-drawable-canvas' в зависимости."
-    )
-
 from pose_detector import PoseDetector
 from skeleton_generator import SkeletonGenerator
 from animation_exporter import AnimationExporter
@@ -34,31 +23,22 @@ def init_page():
         padding: 2rem;
         transition: background-color 0.3s;
     }
-    
-    /* Dark theme */
     [data-theme="dark"] .stApp {
         background-color: #1E1E1E;
         color: #FFFFFF;
     }
-    
-    /* Widget styling */
     .stButton>button {
         background-color: #4CAF50;
         color: white;
         border-radius: 4px;
         padding: 0.5rem 1rem;
     }
-    
     .stDownloadButton>button {
         background-color: #008CBA;
     }
-    
-    /* Progress bars */
     .stProgress > div > div > div {
         background-color: #4CAF50;
     }
-    
-    /* Columns spacing */
     .stColumn {
         padding: 0 1rem;
     }
@@ -86,7 +66,7 @@ def init_page():
         st.session_state.manual_correction = st.sidebar.checkbox("Enable Manual Corrections", value=st.session_state.manual_correction)
         
     if st.session_state.manual_correction:
-        st.sidebar.info("Интерактивное редактирование доступно" + (" (с использованием canvas)" if canvas_available else " (canvas не доступен)"))
+        st.sidebar.info("Интерактивная корректировка временно отключена.")
     
     st.title("Pose Detection & Animation Generator")
     return confidence_threshold
@@ -129,7 +109,7 @@ def main():
         with col1:
             st.subheader("Original")
         with col2:
-            st.subheader("Processed (click to select joint)")
+            st.subheader("Processed")
 
         try:
             if file_type == 'image' and not is_gif:
@@ -151,10 +131,9 @@ def main():
         db.close()
 
 def process_image_upload(uploaded_file, components, processed_file, db, col1, col2):
-    """Обработка изображения с сохранением состояния и интерактивным выбором сустава (если canvas доступен)."""
+    """Обработка изображения с сохранением состояния. Интерактивная коррекция отключена."""
     pose_detector, skeleton_generator, animation_exporter = components
     
-    # Сохраняем исходное изображение в session_state
     if "uploaded_image" not in st.session_state:
         file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
         image = cv2.imdecode(file_bytes, 1)
@@ -165,7 +144,6 @@ def process_image_upload(uploaded_file, components, processed_file, db, col1, co
     with col1:
         st.image(cv2.cvtColor(image, cv2.COLOR_BGR2RGB), use_column_width=True)
     
-    # Обработка изображения для получения позы и скелета
     if "original_skeleton_data" not in st.session_state:
         processed_image, skeleton_data = process_image(image, pose_detector, skeleton_generator)
         st.session_state.original_skeleton_data = skeleton_data
@@ -174,75 +152,15 @@ def process_image_upload(uploaded_file, components, processed_file, db, col1, co
         skeleton_data = st.session_state.original_skeleton_data
         processed_image = st.session_state.processed_image
 
-    # Сохраняем данные поз в БД
     save_pose_data(db, processed_file.id, skeleton_data)
     animation_data_binary = animation_exporter.export_pose(skeleton_data)
     save_animation_data(db, processed_file.id, skeleton_data)
 
     with col2:
-        height, width = processed_image.shape[:2]
         processed_rgb = cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB)
-        pil_image = Image.fromarray(processed_rgb)
-        
-        if canvas_available and st.session_state.get('manual_correction', False):
-            # Используем st_canvas для интерактивного редактирования
-            canvas_result = st_canvas(
-                fill_color="rgba(0, 0, 0, 0)",  # прозрачный фон для рисования
-                stroke_width=5,
-                stroke_color="#FF0000",
-                background_image=pil_image,
-                update_streamlit=True,
-                height=height,
-                width=width,
-                drawing_mode="point",  # режим для регистрации кликов
-                key="canvas"
-            )
-            
-            if canvas_result.json_data is not None:
-                objects = canvas_result.json_data.get("objects", [])
-                if objects:
-                    last_obj = objects[-1]
-                    click_x = last_obj.get("left")
-                    click_y = last_obj.get("top")
-                    
-                    # Находим ближайший joint (координаты нормализованы)
-                    min_dist = float("inf")
-                    selected_joint = None
-                    for joint_name, data in skeleton_data.items():
-                        joint_px = data['position'][0] * width
-                        joint_py = data['position'][1] * height
-                        dist = ((joint_px - click_x)**2 + (joint_py - click_y)**2)**0.5
-                        if dist < min_dist:
-                            min_dist = dist
-                            selected_joint = joint_name
-                    threshold = 20  # порог в пикселях для выбора сустава
-                    if min_dist < threshold:
-                        st.session_state.active_joint = selected_joint
-                        st.write(f"Selected joint: **{selected_joint}**")
-                    else:
-                        st.write("Click closer to a joint to select it.")
-            
-            if st.session_state.get("active_joint"):
-                active_joint = st.session_state.active_joint
-                joints = st.session_state.get("current_landmarks", skeleton_data.copy())
-                st.write(f"Active joint for adjustment: **{active_joint}**")
-                x_pos = st.slider("Adjust X", 0.0, 1.0, float(joints[active_joint]['position'][0]), 0.01, key=f"adj_x_{active_joint}")
-                y_pos = st.slider("Adjust Y", 0.0, 1.0, float(joints[active_joint]['position'][1]), 0.01, key=f"adj_y_{active_joint}")
-                if st.button("Apply Adjustment", key=f"apply_adj_{active_joint}"):
-                    joints[active_joint]['position'] = [x_pos, y_pos]
-                    st.session_state.current_landmarks = joints
-                    corrected_image = pose_detector.draw_corrected_pose(image, joints)
-                    st.session_state.processed_image = corrected_image
-                    corrected_rgb = cv2.cvtColor(corrected_image, cv2.COLOR_BGR2RGB)
-                    st.image(corrected_rgb, use_column_width=True)
-                    st.write(f"Updated {active_joint}: {joints[active_joint]['position']}")
-                if st.button("Save Corrections", key=f"save_adj_{active_joint}"):
-                    save_corrected_pose(db, processed_file.id, joints)
-                    st.success("Corrections saved successfully!")
-        else:
-            # Если canvas недоступен, выводим просто изображение и сообщение
-            st.image(processed_rgb, use_column_width=True)
-            st.info("Интерактивное редактирование недоступно, так как streamlit-drawable-canvas не установлен.")
+        st.image(processed_rgb, use_column_width=True)
+        if st.session_state.get('manual_correction', False):
+            st.info("Интерактивная корректировка временно отключена.")
 
 def process_video_upload(uploaded_file, components, processed_file, db, is_gif, col1, col2):
     """Обработка видео/GIF файлов."""
@@ -307,12 +225,12 @@ def save_corrected_pose(db, file_id: int, joints: dict):
 def show_instructions():
     with st.expander("Instructions"):
         st.markdown("""
-        1. Upload an image/video using the file uploader.
+        1. Upload an image or video using the file uploader.
         2. Wait for processing to complete.
-        3. In the **Processed** panel, click on the preview canvas near a joint to select it.
-        4. Adjust the selected joint using the sliders and click **Apply Adjustment**.
-        5. Click **Save Corrections** to store the changes.
-        6. Download animation data.
+        3. The **Detection Confidence** slider in the sidebar sets the minimum confidence threshold for detecting a pose.
+           A higher value (e.g., 0.7) means that only detections with high certainty are considered, which may improve accuracy.
+        4. The processed image/video will be displayed in the "Processed" panel.
+        5. Download animation data.
         
         Supported formats:
         - Images: JPG, PNG