Update roop/processors/frame/face_enhancer.py

roop/processors/frame/face_enhancer.py

@@ -2,6 +2,8 @@ from typing import Any, List, Callable
 import cv2
 import threading
 import gfpgan
+import os
+import logging
 
 import roop.globals
 import roop.processors.frame.core
@@ -15,6 +17,8 @@ THREAD_SEMAPHORE = threading.Semaphore()
 THREAD_LOCK = threading.Lock()
 NAME = 'ROOP.FACE-ENHANCER'
 
+# Configure logging
+logging.basicConfig(level=logging.INFO)
 
 def get_face_enhancer() -> Any:
     global FACE_ENHANCER
@@ -22,60 +26,93 @@ def get_face_enhancer() -> Any:
     with THREAD_LOCK:
         if FACE_ENHANCER is None:
             model_path = resolve_relative_path('../models/GFPGANv1.4.pth')
-            # todo: set models path https://github.com/TencentARC/GFPGAN/issues/399
-            FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=5) # type: ignore[attr-defined]
+            try:
+                FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=5)  # type: ignore[attr-defined]
+                logging.info(f"Loaded face enhancer model from {model_path}")
+            except Exception as e:
+                logging.error(f"Failed to load face enhancer model: {e}")
+                FACE_ENHANCER = None
     return FACE_ENHANCER
 
-
 def pre_check() -> bool:
     download_directory_path = resolve_relative_path('../models')
-    conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'])
-    return True
-
+    try:
+        conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'])
+        logging.info("Pre-check completed successfully.")
+        return True
+    except Exception as e:
+        logging.error(f"Pre-check failed: {e}")
+        return False
 
 def pre_start() -> bool:
-    if not is_image(roop.globals.target_path) and not is_video(roop.globals.target_path):
-        update_status('Select an image or video for target path.', NAME)
+    try:
+        if not is_image(roop.globals.target_path) and not is_video(roop.globals.target_path):
+            update_status('Select an image or video for target path.', NAME)
+            return False
+        logging.info("Pre-start checks passed.")
+        return True
+    except Exception as e:
+        logging.error(f"Pre-start check failed: {e}")
         return False
-    return True
-
 
 def post_process() -> None:
     global FACE_ENHANCER
 
     FACE_ENHANCER = None
-
+    logging.info("Post-process cleanup done.")
 
 def enhance_face(temp_frame: Frame) -> Frame:
-    with THREAD_SEMAPHORE:
-        _, _, temp_frame = get_face_enhancer().enhance(
-            temp_frame,
-            paste_back=True
-        )
-    return temp_frame
-
+    try:
+        with THREAD_SEMAPHORE:
+            _, _, temp_frame = get_face_enhancer().enhance(
+                temp_frame,
+                paste_back=True
+            )
+        return temp_frame
+    except Exception as e:
+        logging.error(f"Error enhancing face: {e}")
+        return temp_frame  # Return the unmodified frame in case of error
 
 def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
-    target_face = get_one_face(temp_frame)
-    if target_face:
-        temp_frame = enhance_face(temp_frame)
-    return temp_frame
-
+    try:
+        target_face = get_one_face(temp_frame)
+        if target_face:
+            temp_frame = enhance_face(temp_frame)
+        return temp_frame
+    except Exception as e:
+        logging.error(f"Error processing frame: {e}")
+        return temp_frame  # Return the unmodified frame in case of error
 
 def process_frames(source_path: str, temp_frame_paths: List[str], update: Callable[[], None]) -> None:
-    for temp_frame_path in temp_frame_paths:
-        temp_frame = cv2.imread(temp_frame_path)
-        result = process_frame(None, temp_frame)
-        cv2.imwrite(temp_frame_path, result)
-        if update:
-            update()
-
+    try:
+        for temp_frame_path in temp_frame_paths:
+            temp_frame = cv2.imread(temp_frame_path)
+            if temp_frame is None:
+                raise ValueError(f"Failed to read frame from path: {temp_frame_path}")
+            
+            result = process_frame(None, temp_frame)
+            cv2.imwrite(temp_frame_path, result)
+            if update:
+                update()
+        logging.info("Frames processed successfully.")
+    except Exception as e:
+        logging.error(f"Error processing frames: {e}")
 
 def process_image(source_path: str, target_path: str, output_path: str) -> None:
-    target_frame = cv2.imread(target_path)
-    result = process_frame(None, target_frame)
-    cv2.imwrite(output_path, result)
-
+    try:
+        target_frame = cv2.imread(target_path)
+        if target_frame is None:
+            raise ValueError("Failed to read target frame.")
+        
+        result = process_frame(None, target_frame)
+        cv2.imwrite(output_path, result)
+        logging.info(f"Image processed and saved to {output_path}.")
+    except Exception as e:
+        logging.error(f"Error processing image: {e}")
 
 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
-    roop.processors.frame.core.process_video(None, temp_frame_paths, process_frames)
+    try:
+        roop.processors.frame.core.process_video(None, temp_frame_paths, process_frames)
+        logging.info("Video processing completed.")
+    except Exception as e:
+        logging.error(f"Error processing video: {e}")