Significantly improve video resolution/quality using ESPCN_x4 model

2025-03-17 21:31:51 +01:00 · 2024-09-23 02:25:14 +01:00 · 2024-09-23 02:25:14 +01:00 · 1af9abda2f
commit 1af9abda2f
parent 91884eebf7
6 changed files with 231 additions and 4 deletions
--- a/README.md
+++ b/README.md
@ -152,7 +152,7 @@ options:
  -s SOURCE_PATH, --source SOURCE_PATH                     select an source image
  -t TARGET_PATH, --target TARGET_PATH                     select an target image or video
  -o OUTPUT_PATH, --output OUTPUT_PATH                     select output file or directory
-  --frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...]  frame processors (choices: face_swapper, face_enhancer, ...)
+  --frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...]  frame processors (choices: face_swapper, face_enhancer, super_resolution...)
  --keep-fps                                               keep original fps
  --keep-audio                                             keep original audio
  --keep-frames                                            keep temporary frames
@ -166,6 +166,7 @@ options:
  --execution-threads EXECUTION_THREADS                    number of execution threads
  --headless                                               run in headless mode
  --enhancer-upscale-factor                                Sets the upscale factor for the enhancer. Only applies if `face_enhancer` is set as a frame-processor
+  --source-image-scaling-factor                            Set the upscale factor for source images. Only applies if `face_swapper` is set as a frame-processor
  -v, --version                                            show program's version number and exit
 ```

--- a/modules/core.py
+++ b/modules/core.py
@ -51,7 +51,7 @@ def parse_args() -> None:
    program.add_argument('-t', '--target', help='Select a target image or video', dest='target_path')
    program.add_argument('-o', '--output', help='Select output file or directory', dest='output_path')
    program.add_argument('--frame-processor', help='Pipeline of frame processors', dest='frame_processor',
-                         default=['face_swapper'], choices=['face_swapper', 'face_enhancer'], nargs='+')
+                         default=['face_swapper'], choices=['face_swapper', 'face_enhancer', 'super_resolution'], nargs='+')
    program.add_argument('--keep-fps', help='Keep original fps', dest='keep_fps', action='store_true', default=False)
    program.add_argument('--keep-audio', help='Keep original audio', dest='keep_audio', action='store_true', default=True)
    program.add_argument('--keep-frames', help='Keep temporary frames', dest='keep_frames', action='store_true', default=False)
@ -74,6 +74,8 @@ def parse_args() -> None:
    program.add_argument('--enhancer-upscale-factor',
                         help='Sets the upscale factor for the enhancer. Only applies if `face_enhancer` is set as a frame-processor',
                         dest='enhancer_upscale_factor', type=int, default=1)
+    program.add_argument('--source-image-scaling-factor', help='Set the upscale factor for source images',
+                         dest='source_image_scaling_factor', default=2, type=int)
    program.add_argument('-v', '--version', action='version',
                         version=f'{modules.metadata.name} {modules.metadata.version}')

@ -104,6 +106,7 @@ def parse_args() -> None:
    modules.globals.execution_threads = args.execution_threads
    modules.globals.headless = args.headless
    modules.globals.enhancer_upscale_factor = args.enhancer_upscale_factor
+    modules.globals.source_image_scaling_factor = args.source_image_scaling_factor
    # Handle face enhancer tumbler
    modules.globals.fp_ui['face_enhancer'] = 'face_enhancer' in args.frame_processor

--- a/modules/globals.py
+++ b/modules/globals.py
@ -31,3 +31,4 @@ nsfw = None
 camera_input_combobox = None
 webcam_preview_running = False
 enhancer_upscale_factor = 1
+source_image_scaling_factor = 2
--- a/modules/processors/frame/face_swapper.py
+++ b/modules/processors/frame/face_swapper.py
@ -10,6 +10,7 @@ from modules.core import update_status
 from modules.face_analyser import get_one_face, get_many_faces
 from modules.typing import Face, Frame
 from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
+import numpy as np

 FACE_SWAPPER = None
 THREAD_LOCK = threading.Lock()
@ -43,6 +44,22 @@ def get_face_swapper() -> Any:
            FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=modules.globals.execution_providers)
    return FACE_SWAPPER

+def upscale_image(image: np.ndarray, scaling_factor: int = modules.globals.source_image_scaling_factor) -> np.ndarray:
+    """
+    Upscales the given image by the specified scaling factor.
+
+    Args:
+        image (np.ndarray): The input image to upscale.
+        scaling_factor (int): The factor by which to upscale the image.
+
+    Returns:
+        np.ndarray: The upscaled image.
+    """
+    height, width = image.shape[:2]
+    new_size = (width * scaling_factor, height * scaling_factor)
+    upscaled_image = cv2.resize(image, new_size, interpolation=cv2.INTER_CUBIC)
+    return upscaled_image
+
 def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
    return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True)

@ -59,7 +76,14 @@ def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
    return temp_frame

 def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
-    source_face = get_one_face(cv2.imread(source_path))
+    source_image = cv2.imread(source_path)
+    if source_image is None:
+        print(f"Failed to load source image from {source_path}")
+        return
+    # Upscale the source image for better quality
+    source_image_upscaled = upscale_image(source_image, scaling_factor=2)
+    source_face = get_one_face(source_image_upscaled)
+
    for temp_frame_path in temp_frame_paths:
        temp_frame = cv2.imread(temp_frame_path)
        try:
--- a/modules/processors/frame/super_resolution.py
+++ b/modules/processors/frame/super_resolution.py
@ -0,0 +1,198 @@
+import threading
+import traceback
+from typing import Any, List
+import cv2
+
+import os
+
+import modules.globals
+import modules.processors.frame.core
+from modules.core import update_status
+from modules.face_analyser import get_one_face
+from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
+import numpy as np
+
+NAME = 'DLC.SUPER-RESOLUTION'
+THREAD_SEMAPHORE = threading.Semaphore()
+
+# Singleton class for Super-Resolution
+class SuperResolutionModel:
+    _instance = None
+    _lock = threading.Lock()
+
+    def __init__(self, sr_model_path: str = 'ESPCN_x4.pb'):
+        if SuperResolutionModel._instance is not None:
+            raise Exception("This class is a singleton!")
+        self.sr = cv2.dnn_superres.DnnSuperResImpl_create()
+        self.model_path = os.path.join(resolve_relative_path('../models'), sr_model_path)
+        if not os.path.exists(self.model_path):
+            raise FileNotFoundError(f"Super-resolution model not found at {self.model_path}")
+        try:
+            self.sr.readModel(self.model_path)
+            self.sr.setModel("espcn", 4)  # Using ESPCN with 4x upscaling
+        except Exception as e:
+            print(f"Error during super-resolution model initialization: {e}")
+            raise e
+
+    @classmethod
+    def get_instance(cls, sr_model_path: str = 'ESPCN_x4.pb'):
+        if cls._instance is None:
+            with cls._lock:
+                if cls._instance is None:
+                    try:
+                        cls._instance = cls(sr_model_path)
+                    except Exception as e:
+                        print(f"Failed to initialize SuperResolutionModel: {e}")
+                        return None
+        return cls._instance
+
+
+def pre_check() -> bool:
+    """
+    Checks and downloads necessary models before starting the face swapper.
+    """
+    download_directory_path = resolve_relative_path('../models')
+    # Download the super-resolution model as well
+    conditional_download(download_directory_path, [
+        'https://huggingface.co/spaces/PabloGabrielSch/AI_Resolution_Upscaler_And_Resizer/resolve/bcd13b766a9499196e8becbe453c4a848673b3b6/models/ESPCN_x4.pb'
+    ])
+    return True
+
+def pre_start() -> bool:
+    if not is_image(modules.globals.source_path):
+        update_status('Select an image for source path.', NAME)
+        return False
+    elif not get_one_face(cv2.imread(modules.globals.source_path)):
+        update_status('No face detected in the source path.', NAME)
+        return False
+    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
+        update_status('Select an image or video for target path.', NAME)
+        return False
+    return True
+
+
+def apply_super_resolution(image: np.ndarray) -> np.ndarray:
+    """
+    Applies super-resolution to the given image using the provided super-resolver.
+
+    Args:
+        image (np.ndarray): The input image to enhance.
+        sr_model_path (str): ESPCN model path for super-resolution.
+
+    Returns:
+        np.ndarray: The super-resolved image.
+    """
+    with THREAD_SEMAPHORE:
+        sr_model = SuperResolutionModel.get_instance()
+
+        if sr_model is None:
+            print("Super-resolution model is not initialized.")
+            return image
+        try:
+            upscaled_image = sr_model.sr.upsample(image)
+            return upscaled_image
+        except Exception as e:
+            print(f"Error during super-resolution: {e}")
+            return image
+
+
+def process_frame(frame: np.ndarray) -> np.ndarray:
+    """
+    Processes a single frame by swapping the source face into detected target faces.
+
+    Args:
+
+        frame (np.ndarray): The target frame image.
+
+    Returns:
+        np.ndarray: The processed frame with swapped faces.
+    """
+
+    # Apply super-resolution to the entire frame
+    frame = apply_super_resolution(frame)
+
+    return frame
+
+def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
+    """
+    Processes multiple frames by swapping the source face into each target frame.
+
+    Args:
+        source_path (str): Path to the source image.
+        temp_frame_paths (List[str]): List of paths to target frame images.
+        progress (Any, optional): Progress tracker. Defaults to None.
+    """
+    for idx, temp_frame_path in enumerate(temp_frame_paths):
+        frame = cv2.imread(temp_frame_path)
+        if frame is None:
+            print(f"Failed to load frame from {temp_frame_path}")
+            continue
+        try:
+            result = process_frame(frame)
+            cv2.imwrite(temp_frame_path, result)
+        except Exception as exception:
+            traceback.print_exc()
+            print(f"Error processing frame {temp_frame_path}: {exception}")
+        if progress:
+            progress.update(1)
+
+def upscale_image(image: np.ndarray, scaling_factor: int = 2) -> np.ndarray:
+    """
+    Upscales the given image by the specified scaling factor.
+
+    Args:
+        image (np.ndarray): The input image to upscale.
+        scaling_factor (int): The factor by which to upscale the image.
+
+    Returns:
+        np.ndarray: The upscaled image.
+    """
+    height, width = image.shape[:2]
+    new_size = (width * scaling_factor, height * scaling_factor)
+    upscaled_image = cv2.resize(image, new_size, interpolation=cv2.INTER_CUBIC)
+    return upscaled_image
+
+def process_image(source_path: str, target_path: str, output_path: str) -> None:
+    """
+    Processes a single image by swapping the source face into the target image.
+
+    Args:
+        source_path (str): Path to the source image.
+        target_path (str): Path to the target image.
+        output_path (str): Path to save the output image.
+    """
+    source_image = cv2.imread(source_path)
+    if source_image is None:
+        print(f"Failed to load source image from {source_path}")
+        return
+
+    # Upscale the source image for better quality before face detection
+    source_image_upscaled = upscale_image(source_image, scaling_factor=2)
+
+    # Detect source face from the upscaled image
+    source_face = get_one_face(source_image_upscaled)
+    if source_face is None:
+        print("No source face detected.")
+        return
+
+    target_frame = cv2.imread(target_path)
+    if target_frame is None:
+        print(f"Failed to load target image from {target_path}")
+        return
+
+    # Process the frame
+    result = process_frame(target_frame)
+
+    # Save the processed frame
+    cv2.imwrite(output_path, result)
+
+
+def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
+    """
+    Processes a video by swapping the source face into each frame.
+
+    Args:
+        source_path (str): Path to the source image.
+        temp_frame_paths (List[str]): List of paths to video frame images.
+    """
+    modules.processors.frame.core.process_video(None, temp_frame_paths, process_frames)
--- a/requirements.txt
+++ b/requirements.txt
@ -1,7 +1,7 @@
 --extra-index-url https://download.pytorch.org/whl/cu118

 numpy==1.23.5
-opencv-python==4.8.1.78
+opencv-contrib-python==4.10.0.84
 onnx==1.16.0
 insightface==0.7.3
 psutil==5.9.8