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fba6023 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 | from __future__ import annotations
import asyncio
import shutil
import zipfile
from collections.abc import Sequence
from pathlib import Path
from typing import Any
from app.core.exceptions import ProcessingError
from app.models.media import InputMedia, OperationResult
from app.operations.common import execute, output_path, require_inputs, video_codecs
from app.services.ffmpeg_service import FFmpegService
from app.services.validator import bounded_number, positive_int
async def thumbnail(
ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
require_inputs(inputs)
timestamp = bounded_number(params, "timestamp", 0, 0, 86_400)
output = output_path(output_dir, "thumbnail", "jpg")
quality = min(31, positive_int(params, "quality", 3))
return await execute(
ffmpeg,
[
"-ss",
str(timestamp),
"-i",
inputs[0].temp_path,
"-frames:v",
"1",
"-q:v",
str(quality),
output,
],
output,
"video.thumbnail",
{"timestamp": timestamp},
)
async def extract_frames(
ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
require_inputs(inputs)
fps = bounded_number(params, "fps", 1, 0.01, 60)
frame_dir = output_dir / "frames"
frame_dir.mkdir(parents=True, exist_ok=True)
frame_pattern = frame_dir / "frame_%06d.jpg"
args: list[str | Path] = ["-i", inputs[0].temp_path, "-vf", f"fps={fps}", "-q:v", "3"]
maximum = params.get("max_frames")
if maximum is not None:
maximum_value = positive_int(params, "max_frames", 1)
args += ["-frames:v", str(maximum_value)]
args += [frame_pattern]
await ffmpeg.run(args, operation="video.extract_frames")
frames = sorted(frame_dir.glob("frame_*.jpg"))
if not frames:
raise ProcessingError("No frames were extracted")
archive = output_path(output_dir, "frames", "zip")
await asyncio.to_thread(_archive_frames, archive, frames)
await asyncio.to_thread(shutil.rmtree, frame_dir, True)
return OperationResult(
path=archive,
filename=archive.name,
mime_type="application/zip",
metadata={"frames": len(frames), "fps": fps},
)
def _archive_frames(archive: Path, frames: list[Path]) -> None:
with zipfile.ZipFile(archive, "w", zipfile.ZIP_DEFLATED) as zip_file:
for frame in frames:
zip_file.write(frame, frame.name)
async def generate_gif(
ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
require_inputs(inputs)
fps = bounded_number(params, "fps", 10, 1, 30)
width = positive_int(params, "width", 480)
output = output_path(output_dir, "animation", "gif")
palette = output_dir / "palette.png"
await ffmpeg.run(
[
"-i",
inputs[0].temp_path,
"-vf",
f"fps={fps},scale={width}:-1:flags=lanczos,palettegen",
palette,
],
operation="video.gif.palette",
)
await ffmpeg.run(
[
"-i",
inputs[0].temp_path,
"-i",
palette,
"-lavfi",
f"fps={fps},scale={width}:-1:flags=lanczos[x];[x][1:v]paletteuse",
output,
],
operation="video.gif",
)
palette.unlink(missing_ok=True)
if not output.is_file() or output.stat().st_size == 0:
raise ProcessingError("GIF generation did not produce an output")
return OperationResult(
path=output,
filename=output.name,
mime_type="image/gif",
metadata={"fps": fps, "width": width},
)
async def blur_video(
ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
require_inputs(inputs)
strength = min(100, positive_int(params, "strength", 5))
output = output_path(output_dir, "blurred", "mp4")
return await execute(
ffmpeg,
["-i", inputs[0].temp_path, "-vf", f"boxblur={strength}:1", *video_codecs("mp4"), output],
output,
"video.blur",
{"strength": strength},
)
async def sharpen_video(
ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
require_inputs(inputs)
amount = bounded_number(params, "amount", 1.0, 0, 5)
output = output_path(output_dir, "sharpened", "mp4")
return await execute(
ffmpeg,
[
"-i",
inputs[0].temp_path,
"-vf",
f"unsharp=5:5:{amount}:5:5:0",
*video_codecs("mp4"),
output,
],
output,
"video.sharpen",
{"amount": amount},
)
async def denoise_video(
ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
require_inputs(inputs)
output = output_path(output_dir, "denoised", "mp4")
return await execute(
ffmpeg,
["-i", inputs[0].temp_path, "-vf", "hqdn3d", *video_codecs("mp4"), output],
output,
"video.denoise",
)
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