143 lines
4.8 KiB
Python
143 lines
4.8 KiB
Python
import logging
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import os
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import subprocess
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from typing import Dict
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from xml.etree import ElementTree
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import acoustid
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import cv2
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import imagehash
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from PIL import Image
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logger = logging.getLogger("desktopenv.metrics.vlc")
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def is_vlc_playing(actual_status_path: str, rule: Dict[str, str]) -> float:
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"""
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Checks if VLC is currently playing a file.
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"""
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with open(actual_status_path, 'rb') as file:
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actual_status = file.read().decode('utf-8')
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tree = ElementTree.fromstring(actual_status)
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status = tree.find('state').text
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if status == 'playing':
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if rule['type'] == 'file_name':
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file_info = tree.find('information/category[@name="meta"]/info[@name="filename"]').text
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if file_info:
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return 1 if file_info.endswith(rule['file_name']) else 0
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elif rule['type'] == 'url':
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file_info = tree.find('information/category[@name="meta"]/info[@name="url"]').text
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if file_info:
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return 1 if file_info.endswith(rule['url']) else 0
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else:
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logger.error(f"Unknown type: {rule['type']}")
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return 0
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else:
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return 0
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def is_vlc_recordings_folder(actual_config_path: str, rule: Dict[str, str]) -> float:
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"""
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Checks if VLC's recording folder is set to the expected value.
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"""
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with open(actual_config_path, 'rb') as file:
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config_file = file.read().decode('utf-8')
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expected_recording_file_path = rule['recording_file_path']
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try:
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for line in config_file:
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# Skip comments and empty lines
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if line.startswith('#') or not line.strip():
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continue
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# Check if the line contains the recording path setting
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if 'recorded_files_path' in line:
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# Extract the value of the recording path and remove surrounding whitespace
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current_path = line.split('=')[-1].strip()
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# Compare with the Desktop path
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if current_path == expected_recording_file_path:
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return True
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else:
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return False
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# The configuration key was not found in the file
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return False
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except FileNotFoundError:
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logger.error("VLC configuration file not found.")
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return False
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except Exception as e:
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logger.error(f"An error occurred: {e}")
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return False
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def is_vlc_fullscreen(actual_window_size, screen_size):
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if actual_window_size['width'] == screen_size['width'] and actual_window_size['height'] == screen_size['height']:
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return True
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else:
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return False
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def compare_videos(video_path1, video_path2, max_frames_to_check=100, threshold=5):
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# Open both video files
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cap1 = cv2.VideoCapture(video_path1)
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cap2 = cv2.VideoCapture(video_path2)
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frames_checked = 0
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mismatch_count = 0
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while frames_checked < max_frames_to_check:
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# Read frames from both videos
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ret1, frame1 = cap1.read()
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ret2, frame2 = cap2.read()
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# If a video ends, then check if both ended to confirm they are of the same length
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if not ret1 or not ret2:
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return ret1 == ret2
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# Convert frames to PIL Images
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frame1 = Image.fromarray(cv2.cvtColor(frame1, cv2.COLOR_BGR2RGB))
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frame2 = Image.fromarray(cv2.cvtColor(frame2, cv2.COLOR_BGR2RGB))
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# Compute the perceptual hash for each frame
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hash1 = imagehash.phash(frame1)
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hash2 = imagehash.phash(frame2)
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# Increment the frames checked
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frames_checked += 1
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# Compute the difference in the hashes
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if hash1 - hash2 > threshold:
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mismatch_count += 1
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# If there's a significant difference, the frames are not the same
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if mismatch_count > threshold:
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return False
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# If we reach here, the content appears to be the same
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return True
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def are_audio_files_similar(mp3_file_path, mp4_file_path):
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# Extract audio fingerprint from MP3 file
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mp3_fingerprint, mp3_duration = acoustid.fingerprint_file(mp3_file_path)
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# Extract the audio stream from the MP4 file
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mp4_audio_path = os.path.splitext(mp4_file_path)[0] + '_extracted.mp3'
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try:
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subprocess.run(["ffmpeg", "-i", mp4_file_path, "-vn", "-ar", "44100", "-ac", "2", "-ab", "192k", "-f", "mp3",
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mp4_audio_path], check=True)
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except subprocess.CalledProcessError as e:
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print(f"An error occurred during audio extraction from MP4: {e}")
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return False
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# Extract audio fingerprint from the extracted audio
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mp4_fingerprint, mp4_duration = acoustid.fingerprint_file(mp4_audio_path)
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# Clean up temporary extracted audio file
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os.remove(mp4_audio_path)
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# Compare fingerprints (rudimentary comparison)
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if mp3_duration >= mp4_duration and mp3_fingerprint == mp4_fingerprint:
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return True
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return False
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