mirror of
https://github.com/MackinationsAi/UDAV2-ControlNet.git
synced 2026-01-26 23:39:45 +00:00
113 lines
5.4 KiB
Python
113 lines
5.4 KiB
Python
import argparse
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import cv2
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import glob
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import matplotlib
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import numpy as np
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import os
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import torch
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import warnings
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from tqdm import tqdm
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from safetensors.torch import load_file
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# Code upgraded by: MackinationsAi
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from depth_anything_v2.dpt import DepthAnythingV2
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warnings.filterwarnings("ignore", message=".*cudnnStatus.*")
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os.environ['TORCH_CUDNN_V8_API_ENABLED'] = '0'
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def process_video(video_path, output_path, input_size, encoder, pred_only, grayscale):
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DEVICE = 'cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu'
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model_configs = {
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'vits': {'encoder': 'vits', 'features': 64, 'out_channels': [48, 96, 192, 384]},
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'vitb': {'encoder': 'vitb', 'features': 128, 'out_channels': [96, 192, 384, 768]},
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'vitl': {'encoder': 'vitl', 'features': 256, 'out_channels': [256, 512, 1024, 1024]},
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'vitg': {'encoder': 'vitg', 'features': 384, 'out_channels': [1536, 1536, 1536, 1536]}
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}
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depth_anything = DepthAnythingV2(**model_configs[encoder])
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state_dict = load_file(f'checkpoints/depth_anything_v2_{encoder}.safetensors') # Use load_file to load safetensors
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depth_anything.load_state_dict(state_dict)
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depth_anything = depth_anything.to(DEVICE).eval()
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if os.path.isfile(video_path) and video_path.endswith('.mp4'):
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filenames = [video_path]
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else:
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filenames = glob.glob(os.path.join(video_path, '**/*.mp4'), recursive=True)
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os.makedirs(output_path, exist_ok=True)
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margin_width = 26
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cmap = matplotlib.colormaps.get_cmap('Spectral_r')
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for k, filename in enumerate(filenames):
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print(f'Progress {k+1}/{len(filenames)}: {filename}')
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raw_video = cv2.VideoCapture(filename)
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frame_width, frame_height = int(raw_video.get(cv2.CAP_PROP_FRAME_WIDTH)), int(raw_video.get(cv2.CAP_PROP_FRAME_HEIGHT))
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frame_rate = int(raw_video.get(cv2.CAP_PROP_FPS))
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output_width = frame_width * 2 + margin_width
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base_filename = os.path.splitext(os.path.basename(filename))[0]
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combined_output_path = os.path.join(output_path, base_filename + '_combined.mp4')
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depth_output_path = os.path.join(output_path, base_filename + '_depth.mp4')
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grayscale_depth_output_path = os.path.join(output_path, base_filename + '_depth_grayscale.mp4')
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combined_out = cv2.VideoWriter(combined_output_path, cv2.VideoWriter_fourcc(*"mp4v"), frame_rate, (output_width, frame_height))
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depth_out = cv2.VideoWriter(depth_output_path, cv2.VideoWriter_fourcc(*"mp4v"), frame_rate, (frame_width, frame_height))
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grayscale_depth_out = cv2.VideoWriter(grayscale_depth_output_path, cv2.VideoWriter_fourcc(*"mp4v"), frame_rate, (frame_width, frame_height))
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frame_count = int(raw_video.get(cv2.CAP_PROP_FRAME_COUNT))
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for _ in tqdm(range(frame_count), desc="Processing frames", unit="frame"):
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ret, raw_frame = raw_video.read()
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if not ret:
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break
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depth = depth_anything.infer_image(raw_frame, input_size)
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depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255.0
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depth = depth.astype(np.uint8)
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depth_gray = np.repeat(depth[..., np.newaxis], 3, axis=-1)
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grayscale_depth_out.write(depth_gray)
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if not grayscale:
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depth_color = (cmap(depth)[:, :, :3] * 255)[:, :, ::-1].astype(np.uint8)
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depth_out.write(depth_color)
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if not pred_only:
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split_region = np.ones((frame_height, margin_width, 3), dtype=np.uint8) * 255
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combined_frame = cv2.hconcat([raw_frame, split_region, depth_color])
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combined_out.write(combined_frame)
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raw_video.release()
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combined_out.release()
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depth_out.release()
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grayscale_depth_out.release()
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def main():
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while True:
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parser = argparse.ArgumentParser(description='Depth Anything V2')
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parser.add_argument('--video-path', type=str, help='Path to the video file or directory containing videos')
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parser.add_argument('--input-size', type=int, default=518)
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parser.add_argument('--outdir', type=str, default='vis_vid_depth', help='Output directory')
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parser.add_argument('--encoder', type=str, default='vitl', choices=['vits', 'vitb', 'vitl', 'vitg'])
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parser.add_argument('--pred-only', dest='pred_only', action='store_true', help='only display the prediction')
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parser.add_argument('--grayscale', dest='grayscale', action='store_true', help='do not apply colorful palette')
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args = parser.parse_args()
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if not args.video_path:
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args.video_path = input("Please enter the path to the video file or directory containing videos: ").strip()
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if not args.outdir:
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args.outdir = input("Please enter the output directory (default is 'vis_vid_depth'): ").strip() or 'vis_video_depth'
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process_video(args.video_path, args.outdir, args.input_size, args.encoder, args.pred_only, args.grayscale)
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again = input("Would you like to convert another video? Y/N: ").strip().lower()
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if again not in ['y', 'yes']:
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break
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if __name__ == '__main__':
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main() |