64 lines
2.0 KiB
Python
64 lines
2.0 KiB
Python
import numpy as np
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from PIL import Image
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#---------------------------------------------------------#
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# 将图像转换成RGB图像，防止灰度图在预测时报错。
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# 代码仅仅支持RGB图像的预测，所有其它类型的图像都会转化成RGB
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#---------------------------------------------------------#
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def cvtColor(image):
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if len(np.shape(image)) == 3 and np.shape(image)[2] == 3:
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return image
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else:
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image = image.convert('RGB')
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return image
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#---------------------------------------------------#
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# 对输入图像进行resize
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#---------------------------------------------------#
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def resize_image(image, size, letterbox_image):
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iw, ih = image.size
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w, h = size
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if letterbox_image:
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scale = min(w/iw, h/ih)
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nw = int(iw*scale)
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nh = int(ih*scale)
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image = image.resize((nw,nh), Image.BICUBIC)
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new_image = Image.new('RGB', size, (128,128,128))
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new_image.paste(image, ((w-nw)//2, (h-nh)//2))
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else:
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new_image = image.resize((w, h), Image.BICUBIC)
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return new_image
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#---------------------------------------------------#
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# 获得类
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#---------------------------------------------------#
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def get_classes(classes_path):
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with open(classes_path, encoding='utf-8') as f:
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class_names = f.readlines()
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class_names = [c.strip() for c in class_names]
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return class_names, len(class_names)
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def preprocess_input(image):
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image /= 255.0
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image -= np.array([0.485, 0.456, 0.406])
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image /= np.array([0.229, 0.224, 0.225])
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return image
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#---------------------------------------------------#
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# 获得学习率
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#---------------------------------------------------#
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def get_lr(optimizer):
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for param_group in optimizer.param_groups:
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return param_group['lr']
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def show_config(**kwargs):
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print('Configurations:')
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print('-' * 70)
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print('|%25s | %40s|' % ('keys', 'values'))
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print('-' * 70)
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for key, value in kwargs.items():
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print('|%25s | %40s|' % (str(key), str(value)))
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print('-' * 70)
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