20868268100

Committed 09 Jan 2026 11:10PM UTC coverage: 70.585% (-4.1%) from 74.672%

Build # 20868268100

Build Type

Pull #10

github

Committed by

DanielChaseButterfield

Commit Message

Remove tutrle import

Pull Request Pull Request #10: (v0.2) Prototype code for ROS2 Publishing, and new ImageDataOnDisk class

Run Details

508 of 747 new or added lines in 12 files covered. (68.01%)

3 existing lines in 2 files now uncovered.

1411 of 1999 relevant lines covered (70.59%)

1.41 hits per line

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51.92

/src/robotdataprocess/data_types/ImageData/ImageDataOnDisk.py

from __future__ import annotations

from ...conversion_utils import col_to_dec_arr
from .ImageData import ImageData
import numpy as np
from pathlib import Path
from PIL import Image
from typeguard import typechecked
from typing import Union, List

@typechecked
class ImageDataOnDisk(ImageData):

    class LazyImageArray:
        """A read-only array-like interface that loads PNG images from disk on demand."""
        
        height: int
        width: int
        encoding: ImageData.ImageEncoding
        image_paths: List[Path]

        def __init__(self, height: int, width: int, encoding: ImageData.ImageEncoding, image_paths: List[Path]):
            self.height = height
            self.width = width
            self.encoding = encoding
            self.image_paths = image_paths

        def __getitem__(self, idx) -> np.ndarray:
            path: Path = self.image_paths[idx]
            return np.array(Image.open(str(path)), dtype=self.dtype)

        def __setitem__(self, idx, value):
            raise RuntimeError("This LazyPNGArray is read-only; writes are forbidden.")
    
        def __len__(self):
            return len(self.image_paths)

        @property
        def shape(self):
            _, channels = ImageData.ImageEncoding.to_dtype_and_channels(self.encoding)
            if channels == 1:
                return (len(self), self.height, self.width)
            else:
                return (len(self), self.height, self.width, 3)

        @property
        def dtype(self):
            dtype_val, _ = ImageData.ImageEncoding.to_dtype_and_channels(self.encoding)
            return dtype_val
        
    images: ImageDataOnDisk.LazyImageArray # Not initalized here, but put here for visual code highlighting

    def __init__(self, frame_id: str, timestamps: Union[np.ndarray, list], images: ImageDataOnDisk.LazyImageArray):
        super().__init__(frame_id, timestamps, images.height, images.width, images.encoding, images)

    # =========================================================================
    # ============================ Class Methods ============================== 
    # =========================================================================  

    @classmethod
    def from_image_files(cls, image_folder_path: Union[Path, str], frame_id: str) -> ImageDataOnDisk:
        """
        Creates a class structure from a folder with .png files, using the file names
        as the timestamps.

        Args:
            image_folder_path (Path | str): Path to the folder with the images.
            frame_id (str): The frame where this image data was collected.
        Returns:
            ImageDataOnDisk: Instance of this class.
        """

        # Get all png files in the designated folder (sorted)
        all_image_files = [str(p) for p in Path(image_folder_path).glob("*.png")]

        # Extract the timestamps and sort them
        timestamps = col_to_dec_arr([s.split('/')[-1][:-4] for s in all_image_files])
        sorted_indices = np.argsort(timestamps)
        timestamps_sorted = timestamps[sorted_indices]

        # Use sorted_indices to sort all_image_files in the same way
        all_image_files_sorted: List[Path] = [Path(all_image_files[i]) for i in sorted_indices]

        # Make sure the mode is what we expect
        with Image.open(str(all_image_files_sorted[0])) as first_image:
            encoding = ImageData.ImageEncoding.from_pillow_str(first_image.mode)
            if encoding != ImageData.ImageEncoding.RGB8 and encoding != ImageData.ImageEncoding.Mono8:
                raise NotImplementedError(f"Unsupported encoding {encoding} for 'from_image_files' method!")
        
        # Return an ImageDataOnDisk class
        return cls(frame_id, timestamps_sorted, cls.LazyImageArray(first_image.height, first_image.width, encoding, all_image_files_sorted))

1	from __future__ import annotations	2✔
2
3	from ...conversion_utils import col_to_dec_arr	2✔
4	from .ImageData import ImageData	2✔
5	import numpy as np	2✔
6	from pathlib import Path	2✔
7	from PIL import Image	2✔
8	from typeguard import typechecked	2✔
9	from typing import Union, List	2✔
10
11	@typechecked	2✔
12	class ImageDataOnDisk(ImageData):	2✔
13
14	class LazyImageArray:	2✔
15	"""A read-only array-like interface that loads PNG images from disk on demand."""
16
17	height: int	2✔
18	width: int	2✔
19	encoding: ImageData.ImageEncoding	2✔
20	image_paths: List[Path]	2✔
21
22	def __init__(self, height: int, width: int, encoding: ImageData.ImageEncoding, image_paths: List[Path]):	2✔
NEW 23	self.height = height	×
NEW 24	self.width = width	×
NEW 25	self.encoding = encoding	×
NEW 26	self.image_paths = image_paths	×
27
28	def __getitem__(self, idx) -> np.ndarray:	2✔
NEW 29	path: Path = self.image_paths[idx]	×
NEW 30	return np.array(Image.open(str(path)), dtype=self.dtype)	×
31
32	def __setitem__(self, idx, value):	2✔
NEW 33	raise RuntimeError("This LazyPNGArray is read-only; writes are forbidden.")	×
34
35	def __len__(self):	2✔
NEW 36	return len(self.image_paths)	×
37
38	@property	2✔
39	def shape(self):	2✔
NEW 40	_, channels = ImageData.ImageEncoding.to_dtype_and_channels(self.encoding)	×
NEW 41	if channels == 1:	×
NEW 42	return (len(self), self.height, self.width)	×
43	else:
NEW 44	return (len(self), self.height, self.width, 3)	×
45
46	@property	2✔
47	def dtype(self):	2✔
NEW 48	dtype_val, _ = ImageData.ImageEncoding.to_dtype_and_channels(self.encoding)	×
NEW 49	return dtype_val	×
50
51	images: ImageDataOnDisk.LazyImageArray # Not initalized here, but put here for visual code highlighting	2✔
52
53	def __init__(self, frame_id: str, timestamps: Union[np.ndarray, list], images: ImageDataOnDisk.LazyImageArray):	2✔
NEW 54	super().__init__(frame_id, timestamps, images.height, images.width, images.encoding, images)	×
55
56	# =========================================================================
57	# ============================ Class Methods ==============================
58	# =========================================================================
59
60	@classmethod	2✔
61	def from_image_files(cls, image_folder_path: Union[Path, str], frame_id: str) -> ImageDataOnDisk:	2✔
62	"""
63	Creates a class structure from a folder with .png files, using the file names
64	as the timestamps.
65
66	Args:
67	image_folder_path (Path \| str): Path to the folder with the images.
68	frame_id (str): The frame where this image data was collected.
69	Returns:
70	ImageDataOnDisk: Instance of this class.
71	"""
72
73	# Get all png files in the designated folder (sorted)
NEW 74	all_image_files = [str(p) for p in Path(image_folder_path).glob("*.png")]	×
75
76	# Extract the timestamps and sort them
NEW 77	timestamps = col_to_dec_arr([s.split('/')[-1][:-4] for s in all_image_files])	×
NEW 78	sorted_indices = np.argsort(timestamps)	×
NEW 79	timestamps_sorted = timestamps[sorted_indices]	×
80
81	# Use sorted_indices to sort all_image_files in the same way
NEW 82	all_image_files_sorted: List[Path] = [Path(all_image_files[i]) for i in sorted_indices]	×
83
84	# Make sure the mode is what we expect
NEW 85	with Image.open(str(all_image_files_sorted[0])) as first_image:	×
NEW 86	encoding = ImageData.ImageEncoding.from_pillow_str(first_image.mode)	×
NEW 87	if encoding != ImageData.ImageEncoding.RGB8 and encoding != ImageData.ImageEncoding.Mono8:	×
NEW 88	raise NotImplementedError(f"Unsupported encoding {encoding} for 'from_image_files' method!")	×
89
90	# Return an ImageDataOnDisk class
NEW 91	return cls(frame_id, timestamps_sorted, cls.LazyImageArray(first_image.height, first_image.width, encoding, all_image_files_sorted))	×

lunarlab-gatech / robotdataprocess / 20868268100

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