File size: 3,772 Bytes
83e35a7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 |
"""
Fixed keyframe generation that ensures 48 frames are properly extracted
"""
import os
import cv2
import srt
from typing import List
from backend.utils import copy_and_rename_file
def generate_keyframes_fixed(video_path: str, story_subs: List, max_frames: int = 48):
"""
Generate keyframes based on story moments - FIXED VERSION
Args:
video_path: Path to video file
story_subs: List of subtitle objects for key story moments
max_frames: Maximum number of frames to extract (default 48)
"""
print(f"🎯 Generating {len(story_subs)} keyframes (target: {max_frames})")
# Ensure output directory exists
final_dir = "frames/final"
os.makedirs(final_dir, exist_ok=True)
# Clear existing frames
for f in os.listdir(final_dir):
if f.endswith('.png'):
os.remove(os.path.join(final_dir, f))
# Open video
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
print(f"❌ Failed to open video: {video_path}")
return False
fps = cap.get(cv2.CAP_PROP_FPS)
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
print(f"📹 Video: {fps} fps, {total_frames} total frames")
# Extract frames
extracted_count = 0
for i, sub in enumerate(story_subs[:max_frames]):
try:
# Calculate frame position (middle of subtitle duration)
timestamp = (sub.start.total_seconds() + sub.end.total_seconds()) / 2
frame_num = int(timestamp * fps)
# Ensure frame number is valid
frame_num = min(frame_num, total_frames - 1)
# Extract frame
cap.set(cv2.CAP_PROP_POS_FRAMES, frame_num)
ret, frame = cap.read()
if ret and frame is not None:
output_path = os.path.join(final_dir, f"frame{extracted_count:03d}.png")
cv2.imwrite(output_path, frame)
extracted_count += 1
if i % 10 == 0 or i == len(story_subs) - 1:
print(f"✅ Extracted frame {i+1}/{len(story_subs)}: {sub.content[:40]}...")
else:
print(f"⚠️ Failed to extract frame for segment {i+1}")
except Exception as e:
print(f"❌ Error processing segment {i+1}: {e}")
cap.release()
# If we didn't get enough frames, extract more evenly
if extracted_count < max_frames and extracted_count < 10:
print(f"⚠️ Only extracted {extracted_count} frames, extracting more...")
_extract_evenly_distributed_frames(video_path, final_dir, extracted_count, max_frames)
# Final count
final_frames = len([f for f in os.listdir(final_dir) if f.endswith('.png')])
print(f"✅ Total frames in {final_dir}: {final_frames}")
return final_frames > 0
def _extract_evenly_distributed_frames(video_path: str, output_dir: str, start_count: int, target_count: int):
"""Extract frames evenly distributed across the video"""
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
return
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
needed = target_count - start_count
step = total_frames / needed if needed > 0 else 1
count = start_count
for i in range(needed):
frame_num = int(i * step)
cap.set(cv2.CAP_PROP_POS_FRAMES, frame_num)
ret, frame = cap.read()
if ret:
output_path = os.path.join(output_dir, f"frame{count:03d}.png")
cv2.imwrite(output_path, frame)
count += 1
cap.release()
print(f"✅ Extracted {count - start_count} additional frames") |