import subprocess import matplotlib.pyplot as plt import os import statistics import json import csv try: from tqdm import tqdm HAS_TQDM = True except ImportError: HAS_TQDM = False from tkinter import Tk, filedialog # ===== CONFIGURATION ===== VIDEO_FILE = None # Will be selected via file explorer TOLERANCE = 1e-6 # Tolerance for duplicate frame detection DROP_THRESHOLD_MULTIPLIER = 1.5 # Threshold for detecting dropped frames SAVE_PLOT = True # Save plot to PNG instead of just showing EXPORT_JSON = True # Export results to JSON EXPORT_CSV = True # Export results to CSV SHOW_PROGRESS = True # Show progress bar for large files # ========================== def select_video_file(): root = Tk() root.withdraw() # Hide main window file_path = filedialog.askopenfilename( title="Select Video File", filetypes=[("Video files", "*.mp4 *.mkv *.avi *.mov"), ("All files", "*.*")] ) root.destroy() return file_path def get_video_info(video_file): # Extract r_frame_rate, avg_frame_rate, and duration result = subprocess.run( [ "ffprobe", "-v", "0", "-select_streams", "v:0", "-show_entries", "stream=r_frame_rate,avg_frame_rate,duration", "-of", "default=noprint_wrappers=1:nokey=1", video_file ], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True ) if result.returncode != 0: return None, None, None, "Unknown" lines = result.stdout.strip().splitlines() if len(lines) < 3: return None, None, None, "Unknown" def parse_fps(fps_str): try: num, den = fps_str.split('/') return float(num) / float(den) except Exception: return None r_fps = parse_fps(lines[0]) avg_fps = parse_fps(lines[1]) try: duration = float(lines[2]) except Exception: duration = None mode = "Unknown" if r_fps and avg_fps: if abs(r_fps - avg_fps) < 0.01: mode = "CFR" else: mode = "VFR" return r_fps, avg_fps, duration, mode def extract_timestamps(video_file): print("[✓] Extracting timestamps using ffprobe...") result = subprocess.run( [ "ffprobe", "-v", "error", "-select_streams", "v:0", "-show_entries", "frame=pts_time", "-of", "csv=p=0", video_file ], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True ) if result.returncode != 0: print("❌ ffprobe failed:", result.stderr) return [] pts_list = [float(line.strip()) for line in result.stdout.strip().splitlines() if line.strip()] return pts_list def analyze_timestamps(pts_list): if len(pts_list) < 2: print("❌ Not enough frames to analyze.") return [], 0, [], [], [] print(f"[✓] Analyzing {len(pts_list)} frames...") intervals = [] iterable = range(len(pts_list) - 1) if SHOW_PROGRESS and HAS_TQDM and len(pts_list) > 1000: iterable = tqdm(iterable, desc="Analyzing intervals") for i in iterable: intervals.append(pts_list[i+1] - pts_list[i]) valid_intervals = [iv for iv in intervals if iv > 0] if not valid_intervals: print("❌ No valid frame intervals found.") return intervals, 0, [], [], [] expected_interval = statistics.median(valid_intervals) drop_threshold = expected_interval * DROP_THRESHOLD_MULTIPLIER # Detect paused (duplicate) frames paused = [(i, pts_list[i]) for i in range(len(intervals)) if abs(intervals[i]) < TOLERANCE] # Detect dropped frames dropped = [(i, intervals[i]) for i in range(len(intervals)) if intervals[i] > drop_threshold] # Detect out-of-order PTS out_of_order = [(i, pts_list[i], pts_list[i+1]) for i in range(len(pts_list) - 1) if pts_list[i+1] < pts_list[i]] return intervals, expected_interval, paused, dropped, out_of_order def plot_intervals(intervals, expected_interval, drop_threshold): plt.figure(figsize=(12, 5)) plt.plot(intervals, label='Frame Interval (s)', marker='o', linestyle='-') plt.axhline(expected_interval, color='green', linestyle='--', label='Expected Interval') plt.axhline(drop_threshold, color='red', linestyle='--', label='Drop Threshold') plt.xlabel("Frame Number") plt.ylabel("Interval (s)") plt.title("Frame Interval Analysis") plt.legend() plt.grid(True) plt.tight_layout() if SAVE_PLOT: plt.savefig("frame_intervals.png") print("[✓] Plot saved as frame_intervals.png") else: plt.show() def export_results(pts_list, expected_interval, paused, dropped, out_of_order, r_fps, avg_fps, mode, effective_fps, duration, expected_duration): results = { "total_frames": len(pts_list), "r_frame_rate": r_fps, "avg_frame_rate": avg_fps, "effective_fps": effective_fps, "mode": mode, "expected_interval": expected_interval, "video_duration": duration, "expected_duration": expected_duration, "duration_difference": duration - expected_duration if duration and expected_duration else None, "paused_frames": paused, "dropped_frames": dropped, "out_of_order": out_of_order } if EXPORT_JSON: with open("analysis.json", "w") as f: json.dump(results, f, indent=2) print("[✓] Results exported to analysis.json") if EXPORT_CSV: with open("analysis.csv", "w", newline="") as f: writer = csv.writer(f) writer.writerow(["Type", "FrameIndex", "Value1", "Value2"]) for idx, ts in paused: writer.writerow(["Paused", idx, ts, ""]) for idx, gap in dropped: writer.writerow(["Dropped", idx, gap, ""]) for idx, prev_pts, curr_pts in out_of_order: writer.writerow(["OutOfOrder", idx, prev_pts, curr_pts]) print("[✓] Results exported to analysis.csv") def main(): global VIDEO_FILE VIDEO_FILE = select_video_file() if not VIDEO_FILE: print("❌ No file selected.") return if not os.path.isfile(VIDEO_FILE): print(f"❌ File not found: {VIDEO_FILE}") return r_fps, avg_fps, duration, mode = get_video_info(VIDEO_FILE) pts_list = extract_timestamps(VIDEO_FILE) if not pts_list: print("❌ No timestamps extracted.") return intervals, expected_interval, paused, dropped, out_of_order = analyze_timestamps(pts_list) effective_fps = 1 / expected_interval if expected_interval > 0 else None expected_duration = len(pts_list) / effective_fps if effective_fps else None print("\n📋 SUMMARY") print(f"Video file: {VIDEO_FILE}") if r_fps: print(f"Nominal FPS (r_frame_rate): {r_fps:.3f}") if avg_fps: print(f"Average FPS (avg_frame_rate): {avg_fps:.3f}") if effective_fps: print(f"Effective FPS (calculated): {effective_fps:.3f}") print(f"Detected mode: {mode}") if duration: print(f"Video duration (s): {duration:.3f}") if expected_duration: print(f"Expected duration from frames (s): {expected_duration:.3f}") if duration: print(f"Duration difference (s): {duration - expected_duration:.6f}") print(f"Total frames: {len(pts_list)}") print(f"Expected frame interval (median): {expected_interval:.6f} s") print(f"Paused (duplicate PTS) frames: {len(paused)}") print(f"Dropped/irregular frames: {len(dropped)}") print(f"Out-of-order PTS frames: {len(out_of_order)}") if paused: print("\n⏸ Paused frames (same PTS as previous):") for idx, ts in paused[:10]: print(f" Frame {idx} and {idx+1} at {ts:.6f} s") if len(paused) > 10: print(" ...") if dropped: print("\n🕳 Dropped/irregular frame intervals:") for idx, gap in dropped[:10]: print(f" Frame {idx} → {idx+1} gap: {gap:.6f} s") if len(dropped) > 10: print(" ...") if out_of_order: print("\n🔁 Out-of-order PTS detected:") for i, prev_pts, curr_pts in out_of_order[:10]: print(f" Frame {i} PTS: {prev_pts:.6f} > Frame {i+1} PTS: {curr_pts:.6f}") if len(out_of_order) > 10: print(" ...") plot_intervals(intervals, expected_interval, expected_interval * DROP_THRESHOLD_MULTIPLIER) export_results(pts_list, expected_interval, paused, dropped, out_of_order, r_fps, avg_fps, mode, effective_fps, duration, expected_duration) if __name__ == "__main__": main()