{ "__type": "IngestedDoc", "__tag": 4010, "_content": { "Notes": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Note that files are always returned in alphanumerical order. Also note that slicing returns a new " }, { "__type": "CrossRef", "__tag": 4002, "value": "skimage.io.ImageCollection", "reference": { "__type": "RefInfo", "__tag": 4000, "module": "skimage", "version": "*", "kind": "api", "path": "skimage.io.collection:ImageCollection" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": ", " }, { "__type": "Emphasis", "__tag": 4047, "children": [ { "__type": "Text", "__tag": 4046, "value": "not" } ] }, { "__type": "Text", "__tag": 4046, "value": " a view into the data." } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "ImageCollection image loading can be customized through " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_func" }, { "__type": "Text", "__tag": 4046, "value": ". For an ImageCollection " }, { "__type": "InlineCode", "__tag": 4051, "value": "ic" }, { "__type": "Text", "__tag": 4046, "value": ", " }, { "__type": "InlineCode", "__tag": 4051, "value": "ic[5]" }, { "__type": "Text", "__tag": 4046, "value": " calls " }, { "__type": "InlineCode", "__tag": 4051, "value": "load_func(load_pattern[5])" }, { "__type": "Text", "__tag": 4046, "value": " to load that image." } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "For example, here is an ImageCollection that, for each video provided, loads every second frame " } ] }, { "__type": "Code", "__tag": 4050, "value": "import imageio.v3 as iio3\nimport itertools\n\ndef vidread_step(f, step):\n vid = iio3.imiter(f)\n return list(itertools.islice(vid, None, None, step)\n\nvideo_file = 'no_time_for_that_tiny.gif'\nic = ImageCollection(video_file, load_func=vidread_step, step=2)\n\nic # is an ImageCollection object of length 1 because 1 video is provided\n\nx = ic[0]\nx[5] # the 10th frame of the first video", "execution_status": null }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Alternatively, if " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_func" }, { "__type": "Text", "__tag": 4046, "value": " is provided and " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_pattern" }, { "__type": "Text", "__tag": 4046, "value": " is a sequence, an " }, { "__type": "CrossRef", "__tag": 4002, "value": "skimage.io.ImageCollection", "reference": { "__type": "RefInfo", "__tag": 4000, "module": "skimage", "version": "*", "kind": "api", "path": "skimage.io.collection:ImageCollection" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": " of corresponding length will be created, and the individual images will be loaded by calling " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_func" }, { "__type": "Text", "__tag": 4046, "value": " with the matching element of the " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_pattern" }, { "__type": "Text", "__tag": 4046, "value": " as its first argument. In this case, the elements of the sequence do not need to be names of existing files (or strings at all). For example, to create an " }, { "__type": "CrossRef", "__tag": 4002, "value": "skimage.io.ImageCollection", "reference": { "__type": "RefInfo", "__tag": 4000, "module": "skimage", "version": "*", "kind": "api", "path": "skimage.io.collection:ImageCollection" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": " containing 500 images from a video " } ] }, { "__type": "Code", "__tag": 4050, "value": "class FrameReader:\n def __init__ (self, f):\n self.f = f\n def __call__ (self, index):\n return iio3.imread(self.f, index=index)\n\nic = ImageCollection(range(500), load_func=FrameReader('movie.mp4'))\n\nic # is an ImageCollection object of length 500", "execution_status": null }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Another use of " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_func" }, { "__type": "Text", "__tag": 4046, "value": " would be to convert all images to " }, { "__type": "InlineCode", "__tag": 4051, "value": "uint8" }, { "__type": "Text", "__tag": 4046, "value": " " } ] }, { "__type": "Code", "__tag": 4050, "value": "def imread_convert(f):\n return imread(f).astype(np.uint8)\n\nic = ImageCollection('/tmp/*.png', load_func=imread_convert)", "execution_status": null } ], "title": [], "level": 0, "target": null }, "Warns": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Raises": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Yields": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Methods": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Returns": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Summary": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Load and manage a collection of image files." } ] } ], "title": [], "level": 0, "target": null }, "Receives": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Warnings": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Attributes": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Parameters", "__tag": 4026, "children": [ { "__type": "DocParam", "__tag": 4016, "name": "files", "annotation": "list of str", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "If a pattern string is given for " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_pattern" }, { "__type": "Text", "__tag": 4046, "value": ", this attribute stores the expanded file list. Otherwise, this is equal to " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_pattern" }, { "__type": "Text", "__tag": 4046, "value": "." } ] } ] } ] } ], "title": [], "level": 0, "target": null }, "Parameters": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Parameters", "__tag": 4026, "children": [ { "__type": "DocParam", "__tag": 4016, "name": "load_pattern", "annotation": "str or list of str", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Pattern string or list of strings to load. The filename path can be absolute or relative." } ] } ] }, { "__type": "DocParam", "__tag": 4016, "name": "conserve_memory", "annotation": "bool, optional", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "If True, " }, { "__type": "CrossRef", "__tag": 4002, "value": "skimage.io.ImageCollection", "reference": { "__type": "RefInfo", "__tag": 4000, "module": "skimage", "version": "*", "kind": "api", "path": "skimage.io.collection:ImageCollection" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": " does not keep more than one in memory at a specific time. Otherwise, images will be cached once they are loaded." } ] } ] } ] } ], "title": [], "level": 0, "target": null }, "Extended Summary": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Other Parameters": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Parameters", "__tag": 4026, "children": [ { "__type": "DocParam", "__tag": 4016, "name": "load_func", "annotation": "callable", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "InlineCode", "__tag": 4051, "value": "imread" }, { "__type": "Text", "__tag": 4046, "value": " by default. See Notes below." } ] } ] }, { "__type": "DocParam", "__tag": 4016, "name": "**load_func_kwargs", "annotation": "dict", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Any other keyword arguments are passed to " }, { "__type": "ParamRef", "__tag": 4071, "name": "load_func" }, { "__type": "Text", "__tag": 4046, "value": "." } ] } ] } ] } ], "title": [], "level": 0, "target": null } }, "_ordered_sections": [ "Summary", "Extended Summary", "Parameters", "Returns", "Yields", "Receives", "Raises", "Warns", "Other Parameters", "Attributes", "Methods", "Notes", "Warnings" ], "item_file": "/dev/scikit-image/src/skimage/io/collection.py", "item_line": 101, "item_type": "class", "aliases": [ "skimage.io.ImageCollection" ], "example_section_data": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Code", "__tag": 4050, "value": "import imageio.v3 as iio3\nimport skimage.io as io\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\n# Where your images are located\n" }, { "__type": "Code", "__tag": 4050, "value": "data_dir = os.path.join(os.path.dirname(__file__), '../data')\n", "execution_status": "unexpected_exception" }, { "__type": "Text", "__tag": 4046, "value": "\n" }, { "__type": "Code", "__tag": 4050, "value": "coll = io.ImageCollection(data_dir + '/chess*.png')\nlen(coll)\ncoll[0].shape\n", "execution_status": "unexpected_exception" }, { "__type": "Text", "__tag": 4046, "value": "\n" }, { "__type": "Code", "__tag": 4050, "value": "image_col = io.ImageCollection([f'{data_dir}/*.png', '{data_dir}/*.jpg'])\n", "execution_status": "unexpected_exception" }, { "__type": "Text", "__tag": 4046, "value": "\n" }, { "__type": "Code", "__tag": 4050, "value": "class MultiReader:\n def __init__ (self, f):\n self.f = f\n def __call__ (self, index):\n return iio3.imread(self.f, index=index)\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "filename = data_dir + '/no_time_for_that_tiny.gif'\nic = io.ImageCollection(range(24), load_func=MultiReader(filename))\nlen(image_col)\nisinstance(ic[0], np.ndarray)\n", "execution_status": "unexpected_exception" } ], "title": [], "level": 0, "target": null }, "see_also": [], "signature": { "__type": "SignatureNode", "__tag": 4029, "kind": "function", "parameters": [ { "__type": "SigParam", "__tag": 4030, "name": "load_pattern", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": { "__type": "Empty", "__tag": 4031 } }, { "__type": "SigParam", "__tag": 4030, "name": "conserve_memory", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": "True" }, { "__type": "SigParam", "__tag": 4030, "name": "load_func", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": "None" }, { "__type": "SigParam", "__tag": 4030, "name": "load_func_kwargs", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "VAR_KEYWORD", "default": { "__type": "Empty", "__tag": 4031 } } ], "return_annotation": { "__type": "Empty", "__tag": 4031 }, "target_name": "ImageCollection" }, "references": null, "qa": "skimage.io.collection:ImageCollection", "arbitrary": [], "local_refs": [ "**load_func_kwargs", "conserve_memory", "files", "load_func", "load_pattern" ] }