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https://github.com/Laurent2916/REVA-QCAV.git
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56 lines
1.1 KiB
Python
56 lines
1.1 KiB
Python
import PIL
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import numpy as np
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import random
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def get_square(img, pos):
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"""Extract a left or a right square from PILimg shape : (H, W, C))"""
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img = np.array(img)
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h = img.shape[0]
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if pos == 0:
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return img[:, :h]
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else:
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return img[:, -h:]
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def resize_and_crop(pilimg, scale=0.5, final_height=None):
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w = pilimg.size[0]
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h = pilimg.size[1]
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newW = int(w * scale)
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newH = int(h * scale)
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if not final_height:
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diff = 0
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else:
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diff = newH - final_height
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img = pilimg.resize((newW, newH))
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img = img.crop((0, diff // 2, newW, newH - diff // 2))
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return img
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def batch(iterable, batch_size):
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"""Yields lists by batch"""
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b = []
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for i, t in enumerate(iterable):
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b.append(t)
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if (i+1) % batch_size == 0:
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yield b
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b = []
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if len(b) > 0:
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yield b
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def split_train_val(dataset, val_percent=0.05):
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dataset = list(dataset)
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length = len(dataset)
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n = int(length * val_percent)
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random.seed(42)
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random.shuffle(dataset)
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return {'train': dataset[:-n], 'val': dataset[-n:]}
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def normalize(x):
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return x / 255
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