Update app.py

app.py

@@ -5,7 +5,17 @@ import tempfile
 from typing import Optional, Tuple
 from datetime import datetime
 from PIL import Image
-from streamlit_drawable_canvas import st_canvas
+
+# 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
@@ -76,7 +86,7 @@ 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("Click on the preview canvas to select a joint")
+        st.sidebar.info("Интерактивное редактирование доступно" + (" (с использованием canvas)" if canvas_available else " (canvas не доступен)"))
     
     st.title("Pose Detection & Animation Generator")
     return confidence_threshold
@@ -141,7 +151,7 @@ def main():
         db.close()
 
 def process_image_upload(uploaded_file, components, processed_file, db, col1, col2):
-    """Handle image file upload processing with persistent state and interactive joint selection."""
+    """Обработка изображения с сохранением состояния и интерактивным выбором сустава (если canvas доступен)."""
     pose_detector, skeleton_generator, animation_exporter = components
     
     # Сохраняем исходное изображение в session_state
@@ -174,66 +184,68 @@ def process_image_upload(uploaded_file, components, processed_file, db, col1, co
         processed_rgb = cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB)
         pil_image = Image.fromarray(processed_rgb)
         
-        # Отображаем изображение через st_canvas, чтобы можно было кликать по нему.
-        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"
-        )
-        
-        # Если пользователь сделал клик, в canvas_result.json_data появятся объекты.
-        if st.session_state.get('manual_correction', False) and canvas_result.json_data is not None:
-            objects = canvas_result.json_data.get("objects", [])
-            if objects:
-                # Берём последний добавленный объект как клик.
-                last_obj = objects[-1]
-                click_x = last_obj.get("left")
-                click_y = last_obj.get("top")
-                
-                # Находим ближайший joint (учитывая, что координаты суставов 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.")
-        
-        # Если активный joint выбран, показываем слайдеры для его корректировки.
-        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!")
+        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.")
 
 def process_video_upload(uploaded_file, components, processed_file, db, is_gif, col1, col2):
-    """Handle video/GIF file upload processing."""
+    """Обработка видео/GIF файлов."""
     pose_detector, skeleton_generator, animation_exporter = components
     progress_bar = st.progress(0)