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Add support for insta360 single-file format (#1024)
* Add support for insta360 single-file format * Improve some variable names * Add documentation for crop_percentage parameter Co-authored-by: Matthew Tancik <tancik@berkeley.edu>
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cnsumner
GitHub
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@ -48,11 +48,6 @@ def get_insta360_filenames(data: Path) -> Tuple[Path, Path]:
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filename_back = data.parent / stem_back
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filename_front = data.parent / stem_front
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if not filename_back.exists():
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raise FileNotFoundError(f"Could not find {filename_back}")
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if not filename_front.exists():
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raise FileNotFoundError(f"Could not find {filename_front}")
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return filename_back, filename_front
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@ -71,6 +66,8 @@ def convert_insta360_to_images(
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video_back: Path to the back video.
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output_dir: Path to the output directory.
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num_frames_target: Number of frames to extract.
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crop_percentage: Percentage used to calculate the cropped dimentions of extracted frames. Currently used to crop
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out the curved portions of the fish-eye lens.
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verbose: If True, logs the output of the command.
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Returns:
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A tuple containing summary of the conversion and the number of extracted frames.
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@ -123,3 +120,71 @@ def convert_insta360_to_images(
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CONSOLE.log("[bold green]:tada: Done converting insta360 to images.")
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return summary_log, num_final_frames
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def convert_insta360_single_file_to_images(
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video: Path,
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image_dir: Path,
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num_frames_target: int,
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crop_percentage: float = 0.7,
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verbose: bool = False,
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) -> Tuple[List[str], int]:
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"""Converts a video into a sequence of images.
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Args:
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video: Path to the video.
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output_dir: Path to the output directory.
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num_frames_target: Number of frames to extract.
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crop_percentage: Percentage used to calculate the cropped dimentions of extracted frames. Currently used to crop
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out the curved portions of the fish-eye lens.
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verbose: If True, logs the output of the command.
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Returns:
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A tuple containing summary of the conversion and the number of extracted frames.
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"""
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with status(msg="Converting video to images...", spinner="bouncingBall", verbose=verbose):
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# delete existing images in folder
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for img in image_dir.glob("*.png"):
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if verbose:
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CONSOLE.log(f"Deleting {img}")
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img.unlink()
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num_frames = get_num_frames_in_video(video)
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if num_frames == 0:
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CONSOLE.print(f"[bold red]Error: Video has no frames: {video}")
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sys.exit(1)
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spacing = num_frames // (num_frames_target // 2)
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vf_cmds = []
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if spacing > 1:
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vf_cmds = [f"thumbnail={spacing}", "setpts=N/TB"]
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else:
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CONSOLE.print("[bold red]Can't satify requested number of frames. Extracting all frames.")
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vf_cmds_back = vf_cmds.copy()
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vf_cmds_front = vf_cmds.copy()
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vf_cmds_back.append(
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f"crop=ih*{crop_percentage}:ih*{crop_percentage}:ih*({crop_percentage}/4):ih*({crop_percentage}/4)"
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)
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vf_cmds_front.append(
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f"crop=ih*{crop_percentage}:ih*{crop_percentage}:iw/2+ih*{crop_percentage/4}:ih*{crop_percentage/4}"
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)
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front_ffmpeg_cmd = f"ffmpeg -i {video} -vf {','.join(vf_cmds_front)} -r 1 {image_dir / 'frame_%05d.png'}"
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back_ffmpeg_cmd = f"ffmpeg -i {video} -vf {','.join(vf_cmds_back)} -r 1 {image_dir / 'back_frame_%05d.png'}"
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run_command(back_ffmpeg_cmd, verbose=verbose)
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run_command(front_ffmpeg_cmd, verbose=verbose)
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num_extracted_frames = len(list(image_dir.glob("frame*.png")))
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for i, img in enumerate(image_dir.glob("back_frame_*.png")):
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img.rename(image_dir / f"frame_{i+1+num_extracted_frames:05d}.png")
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num_final_frames = len(list(image_dir.glob("*.png")))
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summary_log = []
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summary_log.append(f"Starting with {num_frames} video frames")
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summary_log.append(f"We extracted {num_final_frames} images")
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CONSOLE.log("[bold green]:tada: Done converting insta360 to images.")
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return summary_log, num_final_frames
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@ -2,6 +2,7 @@
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"""Processes a video or image sequence to a nerfstudio compatible dataset."""
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import json
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import sys
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import zipfile
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from dataclasses import dataclass
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@ -246,14 +247,38 @@ class ProcessInsta360:
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filename_back, filename_front = insta360_utils.get_insta360_filenames(self.data)
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# Convert video to images
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summary_log, num_extracted_frames = insta360_utils.convert_insta360_to_images(
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video_front=filename_front,
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video_back=filename_back,
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image_dir=image_dir,
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num_frames_target=self.num_frames_target,
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verbose=self.verbose,
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)
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if not filename_back.exists():
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raise FileNotFoundError(f"Could not find {filename_back}")
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ffprobe_cmd = f"ffprobe -v quiet -print_format json -show_streams -select_streams v:0 {filename_back}"
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ffprobe_output = process_data_utils.run_command(ffprobe_cmd)
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assert ffprobe_output is not None
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ffprobe_decoded = json.loads(ffprobe_output)
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width, height = ffprobe_decoded["streams"][0]["width"], ffprobe_decoded["streams"][0]["height"]
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summary_log, num_extracted_frames = [], 0
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if width / height == 1:
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if not filename_front.exists():
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raise FileNotFoundError(f"Could not find {filename_front}")
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# Convert video to images
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summary_log, num_extracted_frames = insta360_utils.convert_insta360_to_images(
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video_front=filename_front,
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video_back=filename_back,
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image_dir=image_dir,
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num_frames_target=self.num_frames_target,
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verbose=self.verbose,
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)
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else:
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summary_log, num_extracted_frames = insta360_utils.convert_insta360_single_file_to_images(
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video=filename_back,
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image_dir=image_dir,
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num_frames_target=self.num_frames_target,
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verbose=self.verbose,
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)
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# Downscale images
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summary_log.append(process_data_utils.downscale_images(image_dir, self.num_downscales, verbose=self.verbose))
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