如何将输入图像提供给经过训练的模型？预期 input_1 有 4 个维度，但得到的数组形状为 (224, 224, 3)

import tensorflow as tf
from tensorflow import keras
from keras.models import load_model
from keras.preprocessing import image
import numpy as np
import cv2
import matplotlib.pyplot as plt

model=tf.keras.models.load_model('model_ex-024_acc-0.996875.h5')
img_array = cv2.imread('30.jpg')  # convert to array

img_rgb = cv2.cvtColor(img_array, cv2.COLOR_BGR2RGB)

img_rgb = cv2.resize(img_rgb,(224,224),3)
plt.imshow(img_rgb)  # graph it
plt.show()
model.predict(img_rgb)

ValueError: Error when checking input: expected input_1 to have 4 dimensions, but got array with shape (224, 224, 3)

您应该按照模型的预期扩展输入图像的尺寸。你可以使用np.expand_dims。此外，您可能想要缩放图像。

img_rgb = cv2.resize(img_rgb,(224,224),3)  # resize
img_rgb = np.array(img_rgb).astype(np.float32)/255.0  # scaling
img_rgb = np.expand_dims(img_rgb, axis=0)  # expand dimension
y_pred = model.predict(img_rgb) # prediction
y_pred_class = y_pred.argmax(axis=1)[0]

希望它会有所帮助。