如何在数据库中的所有图像中建模预测？

Posted 2023-02-16

【中文标题】如何在数据库中的所有图像中建模预测？

【英文标题】：how to model predict in all images in a DB?

【发布时间】：2021-12-20 05:47:03

【问题描述】：

我建立了一个模型来进行多类语义分割，已经训练过了。但现在我想预测我的 TEST DB 中已经加载的所有图像补丁，并保存输出预测补丁，以便稍后重新组合为完整图像......

我在下面使用此代码，它运行但不保存输出预测图像...运行时指示器会更改行但我在输出上什么也没有...有人可以帮助我吗？对不起我的英语不好

img_number = 1
for image in range(test_images.shape[0]):
input_img = [test_images] #(test_images) e [test_images]roda mais nao salva
y_pred = model.predict(input_img)
y_pred_argmax=np.argmax(y_pred, axis=3)
prediction = y_pred_argmax[image]
cv2.imwrite('/content/drive/MyDrive/BD_filtred/ok'+str(img_number)+".png", prediction) #prediciton
img_number +=1

【参考方案1】：

用于预测测试图像的示例代码。

test_images = ['flower3.jpg', 'flower.jpg', 'flower1.jpg', 'flower2.jpg']

for i in test_images:
  img = tf.keras.utils.load_img(i, target_size=(img_height, img_width))
  img_array = tf.keras.utils.img_to_array(img)
  img_array = tf.expand_dims(img_array, 0) # Create a batch
  predictions = model.predict(img_array)
  score = tf.nn.softmax(predictions[0])

  print(
    "This image most likely belongs to  with a :.2f percent confidence."
    .format(class_names[np.argmax(score)], 100 * np.max(score)))

输出

This image most likely belongs to tulips with a 99.19 percent confidence.
This image most likely belongs to daisy with a 99.84 percent confidence.
This image most likely belongs to roses with a 98.29 percent confidence.
This image most likely belongs to roses with a 98.61 percent confidence.