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import os
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import PIL.Image as Image
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from PIL import ImageFile
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ImageFile.LOAD_TRUNCATED_IMAGES = True
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Image.MAX_IMAGE_PIXELS = None
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def save_file(f_image, save_dir, suffix='.jpg'):
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"""
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Save images with designated suffix
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"""
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f_image = f_image.convert('RGB')
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filepath, _ = os.path.split(save_dir)
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if not os.path.exists(filepath):
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os.makedirs(filepath)
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f_image.save(save_dir + suffix)
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def make_path(file_pack_path):
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if not os.path.exists(file_pack_path):
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os.makedirs(file_pack_path)
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def find_all_files(root, suffix):
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"""
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Return a list of file paths ended with specific suffix
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"""
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res = []
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for root, _, files in os.walk(root):
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for f in files:
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if suffix is not None and not f.endswith(suffix):
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continue
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res.append(os.path.join(root, f))
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print(files)
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return res
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def center_crop(img_size):
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"""
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Return the cropping zone of a non-square image
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:param img_size: img.size
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:return: list that contains the cropping zone
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"""
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width, height = img_size
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a = min(width, height)
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left = int((width - a) / 2)
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top = int((height - a) / 2)
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right = left + a
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bottom = top + a
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return [left, top, right, bottom]
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def data_crop_resize(class_root, output_root, suffix, size=384):
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all_data = find_all_files(class_root, suffix)
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for data_root in all_data:
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if data_root.endswith('.txt'):
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continue
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elif data_root.endswith('.DS_Store'):
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continue
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elif output_root is None:
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new_data_root = (data_root + '_Lite').split('.')[0]
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"""new_data_root = (data_root + '_Lite').replace('.', '_')
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new_data_root = new_data_root.replace('_jpg', '')"""
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else:
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data_name_without_suffix = os.path.split(data_root)[1].split('.')[0]
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new_data_root = os.path.join(output_root, data_name_without_suffix)
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img = Image.open(data_root)
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width, height = img.size
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s = min(width, height)
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"""left = int((width - a) / 2)
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top = int((height - a) / 2)
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right = left + a
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bottom = top + a
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this is DataBiox
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"""
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"""a = int((s * 5) / 7)
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da = int(s / 14)
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top = int(s / 7) + da
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bottom = top + a - 2 * da
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left = int(s / 7) + 4*da
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right = left + a - 2 * da
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this is for P.vivax"""
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"""a = int((s * 5) / 7)
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da = int(s / 14)
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top = int(s / 7) + 3* da
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bottom = top + a - 4 * da
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left = int(s / 7) + 4 * da
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right = left + a - 2 * da
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this is for P_falciparum"""
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a = int((s * 5) / 7)
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da = int(s / 14)
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top = int(s / 7) + 2 * da
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bottom = top + a - 2 * da
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left = int(s / 7) + 4 * da
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right = left + a - 4 * da
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img = img.crop([left, top, right, bottom])
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resized_img = img.resize((int(size), int(size)), Image.ANTIALIAS)
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save_file(resized_img, new_data_root)
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if __name__ == '__main__':
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data_crop_resize(r'F:\Puzzle Tuning Datasets\P.uninfected(NIH-NLM-ThickBloodSmearsU)\NIH-NLM-ThickBloodSmearsU\Uninfected Patients',
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r'D:\CPIA_VersionJournal\CPIA_MJ\S\P_uninfected',
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'tiff',
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384) |
