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import atexit |
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import collections |
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import json |
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import os |
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import io |
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import struct |
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import threading |
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from typing import TYPE_CHECKING |
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import cv2 |
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import numpy as np |
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import torch |
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from diffusers import AutoencoderTiny |
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FILE_UNKNOWN = "Sorry, don't know how to get size for this file." |
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class UnknownImageFormat(Exception): |
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pass |
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types = collections.OrderedDict() |
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BMP = types['BMP'] = 'BMP' |
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GIF = types['GIF'] = 'GIF' |
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ICO = types['ICO'] = 'ICO' |
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JPEG = types['JPEG'] = 'JPEG' |
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PNG = types['PNG'] = 'PNG' |
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TIFF = types['TIFF'] = 'TIFF' |
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image_fields = ['path', 'type', 'file_size', 'width', 'height'] |
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class Image(collections.namedtuple('Image', image_fields)): |
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def to_str_row(self): |
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return ("%d\t%d\t%d\t%s\t%s" % ( |
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self.width, |
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self.height, |
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self.file_size, |
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self.type, |
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self.path.replace('\t', '\\t'), |
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)) |
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def to_str_row_verbose(self): |
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return ("%d\t%d\t%d\t%s\t%s\t##%s" % ( |
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self.width, |
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self.height, |
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self.file_size, |
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self.type, |
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self.path.replace('\t', '\\t'), |
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self)) |
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def to_str_json(self, indent=None): |
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return json.dumps(self._asdict(), indent=indent) |
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def get_image_size(file_path): |
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""" |
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Return (width, height) for a given img file content - no external |
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dependencies except the os and struct builtin modules |
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""" |
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img = get_image_metadata(file_path) |
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return (img.width, img.height) |
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def get_image_size_from_bytesio(input, size): |
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""" |
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Return (width, height) for a given img file content - no external |
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dependencies except the os and struct builtin modules |
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Args: |
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input (io.IOBase): io object support read & seek |
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size (int): size of buffer in byte |
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""" |
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img = get_image_metadata_from_bytesio(input, size) |
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return (img.width, img.height) |
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def get_image_metadata(file_path): |
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""" |
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Return an `Image` object for a given img file content - no external |
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dependencies except the os and struct builtin modules |
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Args: |
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file_path (str): path to an image file |
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Returns: |
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Image: (path, type, file_size, width, height) |
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""" |
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size = os.path.getsize(file_path) |
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with io.open(file_path, "rb") as input: |
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return get_image_metadata_from_bytesio(input, size, file_path) |
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def get_image_metadata_from_bytesio(input, size, file_path=None): |
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""" |
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Return an `Image` object for a given img file content - no external |
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dependencies except the os and struct builtin modules |
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Args: |
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input (io.IOBase): io object support read & seek |
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size (int): size of buffer in byte |
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file_path (str): path to an image file |
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Returns: |
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Image: (path, type, file_size, width, height) |
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""" |
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height = -1 |
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width = -1 |
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data = input.read(26) |
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msg = " raised while trying to decode as JPEG." |
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if (size >= 10) and data[:6] in (b'GIF87a', b'GIF89a'): |
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imgtype = GIF |
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w, h = struct.unpack("<HH", data[6:10]) |
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width = int(w) |
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height = int(h) |
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elif ((size >= 24) and data.startswith(b'\211PNG\r\n\032\n') |
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and (data[12:16] == b'IHDR')): |
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imgtype = PNG |
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w, h = struct.unpack(">LL", data[16:24]) |
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width = int(w) |
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height = int(h) |
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elif (size >= 16) and data.startswith(b'\211PNG\r\n\032\n'): |
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imgtype = PNG |
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w, h = struct.unpack(">LL", data[8:16]) |
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width = int(w) |
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height = int(h) |
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elif (size >= 2) and data.startswith(b'\377\330'): |
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imgtype = JPEG |
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input.seek(0) |
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input.read(2) |
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b = input.read(1) |
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try: |
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while (b and ord(b) != 0xDA): |
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while (ord(b) != 0xFF): |
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b = input.read(1) |
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while (ord(b) == 0xFF): |
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b = input.read(1) |
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if (ord(b) >= 0xC0 and ord(b) <= 0xC3): |
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input.read(3) |
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h, w = struct.unpack(">HH", input.read(4)) |
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break |
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else: |
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input.read( |
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int(struct.unpack(">H", input.read(2))[0]) - 2) |
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b = input.read(1) |
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width = int(w) |
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height = int(h) |
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except struct.error: |
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raise UnknownImageFormat("StructError" + msg) |
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except ValueError: |
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raise UnknownImageFormat("ValueError" + msg) |
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except Exception as e: |
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raise UnknownImageFormat(e.__class__.__name__ + msg) |
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elif (size >= 26) and data.startswith(b'BM'): |
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imgtype = 'BMP' |
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headersize = struct.unpack("<I", data[14:18])[0] |
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if headersize == 12: |
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w, h = struct.unpack("<HH", data[18:22]) |
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width = int(w) |
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height = int(h) |
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elif headersize >= 40: |
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w, h = struct.unpack("<ii", data[18:26]) |
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width = int(w) |
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height = abs(int(h)) |
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else: |
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raise UnknownImageFormat( |
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"Unkown DIB header size:" + |
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str(headersize)) |
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elif (size >= 8) and data[:4] in (b"II\052\000", b"MM\000\052"): |
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imgtype = TIFF |
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byteOrder = data[:2] |
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boChar = ">" if byteOrder == "MM" else "<" |
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tiffTypes = { |
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1: (1, boChar + "B"), |
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2: (1, boChar + "c"), |
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3: (2, boChar + "H"), |
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4: (4, boChar + "L"), |
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5: (8, boChar + "LL"), |
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6: (1, boChar + "b"), |
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7: (1, boChar + "c"), |
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8: (2, boChar + "h"), |
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9: (4, boChar + "l"), |
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10: (8, boChar + "ll"), |
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11: (4, boChar + "f"), |
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12: (8, boChar + "d") |
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} |
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ifdOffset = struct.unpack(boChar + "L", data[4:8])[0] |
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try: |
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countSize = 2 |
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input.seek(ifdOffset) |
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ec = input.read(countSize) |
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ifdEntryCount = struct.unpack(boChar + "H", ec)[0] |
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ifdEntrySize = 12 |
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for i in range(ifdEntryCount): |
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entryOffset = ifdOffset + countSize + i * ifdEntrySize |
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input.seek(entryOffset) |
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tag = input.read(2) |
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tag = struct.unpack(boChar + "H", tag)[0] |
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if (tag == 256 or tag == 257): |
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type = input.read(2) |
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type = struct.unpack(boChar + "H", type)[0] |
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if type not in tiffTypes: |
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raise UnknownImageFormat( |
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"Unkown TIFF field type:" + |
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str(type)) |
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typeSize = tiffTypes[type][0] |
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typeChar = tiffTypes[type][1] |
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input.seek(entryOffset + 8) |
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value = input.read(typeSize) |
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value = int(struct.unpack(typeChar, value)[0]) |
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if tag == 256: |
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width = value |
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else: |
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height = value |
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if width > -1 and height > -1: |
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break |
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except Exception as e: |
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raise UnknownImageFormat(str(e)) |
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elif size >= 2: |
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imgtype = 'ICO' |
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input.seek(0) |
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reserved = input.read(2) |
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if 0 != struct.unpack("<H", reserved)[0]: |
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raise UnknownImageFormat(FILE_UNKNOWN) |
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format = input.read(2) |
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assert 1 == struct.unpack("<H", format)[0] |
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num = input.read(2) |
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num = struct.unpack("<H", num)[0] |
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if num > 1: |
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import warnings |
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warnings.warn("ICO File contains more than one image") |
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w = input.read(1) |
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h = input.read(1) |
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width = ord(w) |
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height = ord(h) |
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else: |
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raise UnknownImageFormat(FILE_UNKNOWN) |
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return Image(path=file_path, |
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type=imgtype, |
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file_size=size, |
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width=width, |
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height=height) |
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import unittest |
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class Test_get_image_size(unittest.TestCase): |
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data = [{ |
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'path': 'lookmanodeps.png', |
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'width': 251, |
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'height': 208, |
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'file_size': 22228, |
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'type': 'PNG'}] |
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def setUp(self): |
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pass |
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def test_get_image_size_from_bytesio(self): |
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img = self.data[0] |
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p = img['path'] |
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with io.open(p, 'rb') as fp: |
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b = fp.read() |
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fp = io.BytesIO(b) |
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sz = len(b) |
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output = get_image_size_from_bytesio(fp, sz) |
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self.assertTrue(output) |
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self.assertEqual(output, |
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(img['width'], |
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img['height'])) |
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def test_get_image_metadata_from_bytesio(self): |
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img = self.data[0] |
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p = img['path'] |
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with io.open(p, 'rb') as fp: |
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b = fp.read() |
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fp = io.BytesIO(b) |
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sz = len(b) |
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output = get_image_metadata_from_bytesio(fp, sz) |
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self.assertTrue(output) |
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for field in image_fields: |
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self.assertEqual(getattr(output, field), None if field == 'path' else img[field]) |
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def test_get_image_metadata(self): |
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img = self.data[0] |
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output = get_image_metadata(img['path']) |
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self.assertTrue(output) |
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for field in image_fields: |
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self.assertEqual(getattr(output, field), img[field]) |
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def test_get_image_metadata__ENOENT_OSError(self): |
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with self.assertRaises(OSError): |
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get_image_metadata('THIS_DOES_NOT_EXIST') |
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def test_get_image_metadata__not_an_image_UnknownImageFormat(self): |
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with self.assertRaises(UnknownImageFormat): |
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get_image_metadata('README.rst') |
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def test_get_image_size(self): |
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img = self.data[0] |
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output = get_image_size(img['path']) |
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self.assertTrue(output) |
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self.assertEqual(output, |
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(img['width'], |
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img['height'])) |
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def tearDown(self): |
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pass |
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def main(argv=None): |
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""" |
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Print image metadata fields for the given file path. |
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Keyword Arguments: |
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argv (list): commandline arguments (e.g. sys.argv[1:]) |
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Returns: |
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int: zero for OK |
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""" |
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import logging |
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import optparse |
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import sys |
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prs = optparse.OptionParser( |
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usage="%prog [-v|--verbose] [--json|--json-indent] <path0> [<pathN>]", |
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description="Print metadata for the given image paths " |
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"(without image library bindings).") |
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prs.add_option('--json', |
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dest='json', |
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action='store_true') |
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prs.add_option('--json-indent', |
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dest='json_indent', |
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action='store_true') |
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prs.add_option('-v', '--verbose', |
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dest='verbose', |
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action='store_true', ) |
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prs.add_option('-q', '--quiet', |
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dest='quiet', |
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action='store_true', ) |
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prs.add_option('-t', '--test', |
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dest='run_tests', |
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action='store_true', ) |
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argv = list(argv) if argv is not None else sys.argv[1:] |
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(opts, args) = prs.parse_args(args=argv) |
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loglevel = logging.INFO |
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if opts.verbose: |
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loglevel = logging.DEBUG |
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elif opts.quiet: |
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loglevel = logging.ERROR |
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logging.basicConfig(level=loglevel) |
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log = logging.getLogger() |
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log.debug('argv: %r', argv) |
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log.debug('opts: %r', opts) |
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log.debug('args: %r', args) |
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if opts.run_tests: |
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import sys |
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sys.argv = [sys.argv[0]] + args |
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import unittest |
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return unittest.main() |
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output_func = Image.to_str_row |
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if opts.json_indent: |
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import functools |
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output_func = functools.partial(Image.to_str_json, indent=2) |
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elif opts.json: |
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output_func = Image.to_str_json |
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elif opts.verbose: |
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output_func = Image.to_str_row_verbose |
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EX_OK = 0 |
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EX_NOT_OK = 2 |
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if len(args) < 1: |
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prs.print_help() |
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print('') |
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prs.error("You must specify one or more paths to image files") |
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errors = [] |
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for path_arg in args: |
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try: |
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img = get_image_metadata(path_arg) |
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print(output_func(img)) |
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except KeyboardInterrupt: |
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raise |
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except OSError as e: |
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log.error((path_arg, e)) |
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errors.append((path_arg, e)) |
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except Exception as e: |
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log.exception(e) |
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errors.append((path_arg, e)) |
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pass |
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if len(errors): |
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import pprint |
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print("ERRORS", file=sys.stderr) |
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print("======", file=sys.stderr) |
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print(pprint.pformat(errors, indent=2), file=sys.stderr) |
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return EX_NOT_OK |
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return EX_OK |
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is_window_shown = False |
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display_lock = threading.Lock() |
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current_img = None |
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update_event = threading.Event() |
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def update_image(img, name): |
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global current_img |
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with display_lock: |
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current_img = (img, name) |
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update_event.set() |
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def display_image_in_thread(): |
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global is_window_shown |
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def display_img(): |
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global current_img |
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while True: |
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update_event.wait() |
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with display_lock: |
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if current_img: |
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img, name = current_img |
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cv2.imshow(name, img) |
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current_img = None |
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update_event.clear() |
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if cv2.waitKey(1) & 0xFF == 27: |
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cv2.destroyAllWindows() |
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print('\nESC pressed, stopping') |
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break |
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if not is_window_shown: |
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is_window_shown = True |
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threading.Thread(target=display_img, daemon=True).start() |
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def show_img(img, name='AI Toolkit'): |
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img = np.clip(img, 0, 255).astype(np.uint8) |
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update_image(img[:, :, ::-1], name) |
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if not is_window_shown: |
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display_image_in_thread() |
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def show_tensors(imgs: torch.Tensor, name='AI Toolkit'): |
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if len(imgs.shape) == 4: |
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img_list = torch.chunk(imgs, imgs.shape[0], dim=0) |
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else: |
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img_list = [imgs] |
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img = torch.cat(img_list, dim=3) |
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img = img / 2 + 0.5 |
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img_numpy = img.to(torch.float32).detach().cpu().numpy() |
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img_numpy = np.clip(img_numpy, 0, 1) * 255 |
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img_numpy = img_numpy.transpose(0, 2, 3, 1) |
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img_numpy = img_numpy.astype(np.uint8) |
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show_img(img_numpy[0], name=name) |
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def show_latents(latents: torch.Tensor, vae: 'AutoencoderTiny', name='AI Toolkit'): |
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if vae.device == 'cpu': |
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vae.to(latents.device) |
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latents = latents / vae.config['scaling_factor'] |
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imgs = vae.decode(latents).sample |
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show_tensors(imgs, name=name) |
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def on_exit(): |
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if is_window_shown: |
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cv2.destroyAllWindows() |
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def reduce_contrast(tensor, factor): |
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factor = max(0, min(factor, 1)) |
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mean = torch.mean(tensor) |
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adjusted_tensor = (tensor - mean) * factor + mean |
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return torch.clamp(adjusted_tensor, -1.0, 1.0) |
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atexit.register(on_exit) |
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if __name__ == "__main__": |
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import sys |
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sys.exit(main(argv=sys.argv[1:])) |
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