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fix: optimize video stabilization with adaptive zoom and single-pass encoding

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Michael committed 2026-01-29 12:15:09 +01:00
1 parent d7377914e7
commit 15397974e0
1 file changed
+54 -89
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ffmpeg-service/main.py
+54 -89
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@@ -433,94 +433,48 @@ async def process_reel(request: ReelRequest, x_api_key: str = Header(None)):
stats["tts_duration"] = time.time() - start_step
start_step = time.time()
# 3.5 Stabilize video if requested (vidstab two-pass)
# 4. Build FFmpeg Command with Unified filter_complex
cmd = ["ffmpeg", "-y", "-i", str(input_video_path)]
# --- Stability Pass 1 (if requested) ---
vidstab_filter = ""
if request.stabilize:
print("📐 Starting video stabilization (vidstab)...")
print("📐 Starting video stabilization (Pass 1: Detection)...")
transforms_path = job_dir / "transforms.trf"
stabilized_path = job_dir / "stabilized.mp4"
try:
# Pass 1: Detect motion/shakiness
print("📐 Pass 1: Detecting motion...")
detect_cmd = [
"ffmpeg",
"-y",
"-i",
str(input_video_path),
"-vf",
f"vidstabdetect=stepsize=6:shakiness=8:accuracy=9:result={transforms_path}",
"-f",
"null",
"-",
]
detect_proc = subprocess.run(
detect_cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE
# Run detection pass
detect_cmd = [
"ffmpeg",
"-y",
"-i",
str(input_video_path),
"-vf",
f"vidstabdetect=stepsize=6:shakiness=8:accuracy=9:result={transforms_path}",
"-f",
"null",
"-",
]
detect_proc = subprocess.run(
detect_cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE
)
if detect_proc.returncode == 0 and transforms_path.exists():
print(
"✅ Stabilization Pass 1 complete. Integrating Pass 2 into main filter chain."
)
# We will add vidstabtransform to the video chain below
# optzoom=2 -> Adaptive zoom to avoid black borders
# zoom=0 -> Auto zoom
vidstab_filter = f"vidstabtransform=input={transforms_path}:smoothing=10:optzoom=2:zoom=0:interpol=bicubic,unsharp=5:5:0.8:3:3:0.4,"
else:
print(
f"⚠️ Stabilization Pass 1 failed: {detect_proc.stderr.decode()[:500]}"
)
if detect_proc.returncode != 0:
print(
f"⚠️ Stabilization pass 1 failed: {detect_proc.stderr.decode()[:500]}"
)
elif transforms_path.exists():
# Pass 2: Apply stabilization transform
print("📐 Pass 2: Applying stabilization...")
transform_cmd = [
"ffmpeg",
"-y",
"-i",
str(input_video_path),
"-vf",
f"vidstabtransform=input={transforms_path}:smoothing=10:crop=black:zoom=1,unsharp=5:5:0.8:3:3:0.4",
"-c:v",
"libx264",
"-profile:v",
"high",
"-r",
"30",
"-preset",
"medium",
"-crf",
"17",
"-b:v",
"10M",
"-maxrate",
"12M",
"-bufsize",
"20M",
"-c:a",
"copy",
str(stabilized_path),
]
transform_proc = subprocess.run(
transform_cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE
)
if transform_proc.returncode == 0 and stabilized_path.exists():
# Use stabilized video for further processing
input_video_path = stabilized_path
print("✅ Video stabilization complete!")
else:
print(
f"⚠️ Stabilization pass 2 failed: {transform_proc.stderr.decode()[:500]}"
)
else:
print("⚠️ Transforms file not created, skipping stabilization")
except Exception as e:
print(f"⚠️ Stabilization error (continuing without): {e}")
stats["stabilize_duration"] = time.time() - start_step
start_step = time.time()
# 4. Build FFmpeg Command
cmd = ["ffmpeg", "-y", "-i", str(input_video_path)]
video_filters = []
audio_filters = []
# 4. Build FFmpeg Command with Unified filter_complex
cmd = ["ffmpeg", "-y", "-i", str(input_video_path)]
# --- Audio Checks ---
has_original_audio = False
try:
@@ -565,10 +519,20 @@ async def process_reel(request: ReelRequest, x_api_key: str = Header(None)):
fc_parts = []
# A. Video Chain
# 1. Scale & Crop to Fill 1080x1920 (Vertical Reel)
# [0:v] -> [v_processed]
# Using 'increase' + 'crop' to ensure full screen coverage without black bars
video_filters_str = "scale=1080:1920:force_original_aspect_ratio=increase,crop=1080:1920,unsharp=5:5:0.8:3:3:0.4"
# Chain: [0:v] -> [stabilize] -> [scale/crop] -> [text] -> [vout]
# 1. Stabilization (if enabled) + Scaling/Cropping
# We apply stabilization FIRST on raw video, THEN crop to 9:16
# Start of video chain
v_chain = "[0:v]"
if vidstab_filter:
v_chain += vidstab_filter
# Note: vidstabtransform output is same res as input
# Scale & Crop to Fill 1080x1920 (Vertical Reel)
v_chain += "scale=1080:1920:force_original_aspect_ratio=increase,crop=1080:1920"
# 2. Text Overlay
if request.text and request.draw_text:
@@ -577,7 +541,7 @@ async def process_reel(request: ReelRequest, x_api_key: str = Header(None)):
# Subtitles (TikTok style) using ASS (already generated in TTS block)
print(f"🎬 Overlaying subtitles from TTS ASS: {tts_ass_path}")
ass_path_str = str(tts_ass_path).replace("\\", "/").replace(":", "\\:")
text_filter = f"subtitles='{ass_path_str}'"
text_filter = f",subtitles='{ass_path_str}'"
else:
# Standard Text (without TTS)
print(
@@ -588,13 +552,14 @@ async def process_reel(request: ReelRequest, x_api_key: str = Header(None)):
generate_simple_ass(request.text, std_ass_path, font_size=40)
ass_path_str = str(std_ass_path).replace("\\", "/").replace(":", "\\:")
text_filter = f"subtitles='{ass_path_str}'"
text_filter = f",subtitles='{ass_path_str}'"
# Combine formatting + text
video_filters_str += f",{text_filter}"
v_chain += text_filter
# Define Video Chain
fc_parts.append(f"[0:v]{video_filters_str}[vout]")
# End of video chain
v_chain += "[vout]"
fc_parts.append(v_chain)
# B. Audio Chain
audio_mapped = False