Add cuda utilization and cuda memory to progress bar
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21e2953420
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@ -1,10 +1,12 @@
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import os
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from tqdm import tqdm
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import torch
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import onnxruntime
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import cv2
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import insightface
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import roop.globals
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from roop.analyser import get_face_single, get_face_many
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import onnxruntime
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FACE_SWAPPER = None
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@ -29,23 +31,17 @@ def swap_face_in_frame(source_face, target_face, frame):
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return frame
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def process_faces(source_face, frame, progress):
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def process_faces(source_face, target_frame, progress):
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if roop.globals.all_faces:
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many_faces = get_face_many(frame)
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many_faces = get_face_many(target_frame)
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if many_faces:
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for face in many_faces:
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frame = swap_face_in_frame(source_face, face, frame)
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progress.set_postfix(status='.', refresh=True)
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target_frame = swap_face_in_frame(source_face, face, target_frame)
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else:
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progress.set_postfix(status='S', refresh=True)
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else:
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face = get_face_single(frame)
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face = get_face_single(target_frame)
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if face:
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frame = swap_face_in_frame(source_face, face, frame)
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progress.set_postfix(status='.', refresh=True)
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else:
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progress.set_postfix(status='S', refresh=True)
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return frame
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target_frame = swap_face_in_frame(source_face, face, target_frame)
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return target_frame
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def process_video(source_img, frame_paths):
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@ -54,12 +50,13 @@ def process_video(source_img, frame_paths):
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with tqdm(total=len(frame_paths), desc="Processing", unit="frame", dynamic_ncols=True, bar_format=progress_bar_format) as progress:
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for frame_path in frame_paths:
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if roop.globals.gpu_vendor == 'nvidia':
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progress.set_postfix(cuda_utilization="{:02d}%".format(torch.cuda.utilization()), cuda_memory="{:02d}GB".format(torch.cuda.memory_usage()))
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frame = cv2.imread(frame_path)
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try:
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result = process_faces(source_face, frame, progress)
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cv2.imwrite(frame_path, result)
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except Exception:
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progress.set_postfix(status='E', refresh=True)
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pass
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progress.update(1)
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