import cv2
import numpy as np
from pathlib import Path
import time
from tqdm import tqdm
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--Input", type=str)
parser.add_argument("-o", "--Output", type=str, default="output.mp4")
parser.add_argument("-t", "--Target", type=str)
args = parser.parse_args()
start_time = time.time()
img = cv2.imread(str(Path(args.Target)), cv2.IMREAD_COLOR)
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img = cv2.resize(img, (224, 224))
ssim_algo = cv2.quality.QualitySSIM_create(img)
cap = cv2.VideoCapture(str(Path(args.Input)))
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
video_fps = cap.get(cv2.CAP_PROP_FPS)
print(f"Video FPS: {video_fps:.2f}, Total frames: {total_frames}, Video length: {(total_frames / video_fps):.2f} seg")
pbar = tqdm(
total=total_frames,
bar_format="{desc}", # only render the description
desc="aFPS: 0.00" # initial text
)
prev = time.perf_counter()
best_match = -1
frameCouter = 0
best_match_frame = 0
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
frameCouter += 1
try:
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
frame = cv2.resize(frame, (224, 224))
sim = ssim_algo.compute(frame)[0]
if sim > best_match:
best_match = sim
best_match_frame = frameCouter
except Exception as e:
continue
finally:
now = time.perf_counter()
fps = 1.0 / (now - prev)
prev = now
pbar.set_description(f"aFPS: {fps:.2f}, best Match. {best_match_frame} / {best_match:.2f}; Aprox timestamp {(best_match_frame / video_fps):.4f}")
pbar.update(1)
pbar.close()
cap.release()
end_time = time.time()
print(f"{end_time - start_time:.4f} seconds")