Upload test.py

test.py

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+from datetime import date
+import jittor as jt
+from numpy.core.fromnumeric import shape
+from numpy.lib.type_check import imag
+from model import Model
+from jittor.dataset.mnist import MNIST
+import jittor.transform as trans
+import numpy as np
+import cv2
+import os
+
+
+def ImageClassification(img_path, model):
+    # 得到一个 HxWx3 的 array(224, 225, 3)
+    image_start = cv2.imread(img_path)
+    # 把图像缩放到 28x28 个像素(28, 28, 3)
+    image = cv2.resize(image_start, (28, 28))
+    # print(image.shape)
+    image = image / 255.0               # 把图像的 RGB 值从 [0, 255] 变为 [0, 1]
+    image = image.transpose(2, 0, 1)    # 把输入格式从 HWC 改为 CHW
+    image = jt.float32(image)           # 变为 Jittor Var
+    image_end = image.unsqueeze(dim=0)      # 加入 batch 维度，变为 [1, C, H, W]
+    outputs = model(image_end)
+    prediction = np.argmax(outputs.data, axis=1)
+    # TODO 展示图片
+    cv2.imshow('MNISt', image_start)
+    cv2.waitKey(0)
+    print('图片识别结果：'+str(prediction[0]))
+
+
+def main():
+    pwd_path = os.path.abspath(os.path.dirname(__file__))
+    save_model_path = os.path.join(pwd_path, 'model/mnist_model.pkl')
+    # TODO 加载模型
+    model = Model()
+    model.load_parameters(jt.load(save_model_path))
+    # TODO 加载本地图片
+    img_path = '0.jpg'
+    # TODO 对图片进行识别
+    ImageClassification(img_path, model)
+
+
+if __name__ == '__main__':
+    main()