82 lines
2.0 KiB
Python
Executable File
82 lines
2.0 KiB
Python
Executable File
import cv2
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from PIL import Image
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import matplotlib as mpl
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from src.utils.load_emnist import *
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def get_mapping(num, with_type='letters'):
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"""
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根据 mapping，由传入的 num 计算 UTF8 字符。详见 README.md
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:param num:
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:param with_type:
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:return:
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"""
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if with_type == 'byclass':
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if num <= 9:
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return chr(num + 48) # 数字
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elif num <= 35:
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return chr(num + 55) # 大写字母
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else:
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return chr(num + 61) # 小写字母
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elif with_type == 'letters':
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return chr(num + 64) + " / " + chr(num + 96) # 大写/小写字母
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elif with_type == 'digits':
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return chr(num + 96)
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else:
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return num
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def show_pred_result(path, result):
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"""
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可视化的方式展示图片和预测结果
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:param path: 图片路径
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:param result: 预测结果
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:return: None
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"""
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mpl.rcParams['font.sans-serif'] = ['SimHei'] # 中文字体支持
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img = Image.open(path)
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plt.figure(path) # 文件路径作窗口标题
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plt.axis('off') # 关闭坐标系显示
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plt.title("预测结果是：" + result)
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plt.imshow(img)
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plt.show()
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def show_data_set(images_data, num=1000):
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"""
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转换数据集中的内容并在窗口中展示
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:param images_data:
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:param num: 展示几个
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:return: None
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"""
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images = []
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img = []
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for i in range(images_data.shape[0]):
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im = images_data[i]
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im = im.reshape(28, 28)
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if len(img) == 0:
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img = im
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else:
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# 横向组合
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img = np.hstack((img, im))
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# 每行显示30个数字图片
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if img.shape[1] / 28 == 45:
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if len(images) == 0:
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images = img.copy()
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img = []
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else:
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# 纵向组合
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images = np.vstack((images, img))
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img = []
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# 显示前 num 个
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if i == num:
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break
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cv2.imshow('data_set_visualization', images)
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cv2.waitKey()
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cv2.destroyAllWindows()
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