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import cv2
import numpy as np
import os
from tqdm import tqdm
import re
import concurrent.futures
def get_video_duration(stderr_output):
"""Get the duration of a video using ffmpeg."""
ffmpeg_output = stderr_output
match = re.search(r"Duration: (\d{2}):(\d{2}):(\d{2})\.(\d{2})", ffmpeg_output, re.IGNORECASE)
if match:
hours = int(match.group(1))
minutes = int(match.group(2))
seconds = int(match.group(3))
milliseconds = int(match.group(4))
total_seconds = hours * 3600 + minutes * 60 + seconds + milliseconds / 100
return total_seconds
else:
print("Duration not found in ffmpeg output.")
return 0
def get_video_dimensions(stderr_output):
"""Extract video width and height from ffmpeg stderr output."""
match = re.search(r'(\d{3,4})x(\d{3,4})', stderr_output)
if match:
width = int(match.group(1))
height = int(match.group(2))
return width, height
return None, None
def get_video_fps(stderr_output):
"""Extract video frame rate from ffmpeg stderr output."""
match = re.search(r'(\d+(\.\d+)?) fps', stderr_output)
if match:
fps = float(match.group(1))
return fps
return None
def calculate_mse(frame1, frame2):
"""Calculate Mean Squared Error between two frames."""
frame1 = cv2.resize(frame1, (frame2.shape[1], frame2.shape[0])) # Ensure consistent dimensions
mse = np.sum((frame1 - frame2) ** 2) / float(frame1.size) # Compute MSE
return mse
def is_static(mse, threshold=5): # Using slightly lower threshold
"""Determine if frame is static based on MSE threshold."""
return mse < threshold # Frame considered static if MSE below threshold
def load_frame(frame_path):
"""Load a frame and convert to grayscale."""
frame = cv2.imread(frame_path)
if frame is None:
return None # Return None if frame loading fails
return cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
def detect_static_video(frame_path, frame_count=20):
"""Detect if video is static by analyzing frame differences."""
try:
static_frame_count = 0
sample_count = 0
# Generate frame file paths
frame_paths = [os.path.join(frame_path, f'{frame_index*4:06d}.jpg')
for frame_index in range(1, frame_count + 1)]
# Parallel frame loading using multithreading
with concurrent.futures.ThreadPoolExecutor() as executor:
frames = list(executor.map(load_frame, frame_paths))
# Filter out failed frame loads
frames = [frame for frame in frames if frame is not None]
# Require minimum 2 frames for analysis
if len(frames) < 2:
return False # Insufficient frames for static detection
# Count static frames
prev_frame = frames[0]
for gray_frame in frames[1:]:
mse = calculate_mse(prev_frame, gray_frame)
if is_static(mse):
static_frame_count += 1
prev_frame = gray_frame # Update previous frame
# Calculate static frame ratio
sample_count = len(frames) # Actual processed frame count
static_ratio = static_frame_count / sample_count if sample_count > 0 else 0
# Video considered static if >85% frames are static
return static_ratio > 0.85
except Exception as e:
print(f"Error processing video: {frame_path}, Error: {e}")
return None # Return None to indicate error
def process_video_folder(folder_path, output_file, error_log):
"""Batch process video folders for static detection."""
video_files = [f for f in os.listdir(folder_path)
if re.search(r'^[a-zA-Z0-9_-]*_.\d*0$', f)]
with open(output_file, 'w') as output:
for idx, video_file in enumerate(tqdm(video_files, desc="Processing Videos", unit="file")):
frame_path = os.path.join(folder_path, video_file)
result = detect_static_video(frame_path)
if result is None:
# Log failed processing attempts
with open(error_log, 'a') as error_output:
error_output.write(f"Error processing: {video_file}\n")
elif result:
output.write(f"{video_file}\n") # Record static video filename
print(f"{video_file} is static")
# Example usage
if __name__ == "__main__":
folder_path = '' # Video frame directory
output_file = './static_new.txt' # Static video output list
error_log = './static_new_err.txt' # Error log file
process_video_folder(folder_path, output_file, error_log) |