问题描述
我是 VGG19 和 Python 图像处理的新手。我正在尝试测试我训练的 VGG19 模型来预测图像。我收到此错误:-
ValueError: Input 0 is incompatible with layer functional_3: expected shape=(None,224,3),found shape=(None,240,3)
我用于预测的 tensorflow 代码是:-
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
import numpy as np
import cv2
import tensorflow as tf
from tensorflow.keras.models import load_model
model = load_model('VGG19.h5')
CATEGORIES = ["Pneumonia","Non-Pneumonia"]
img = cv2.imread('person1_bacteria_1.jpeg')
img = cv2.resize(img,(240,240)) # resize image to match model's expected sizing
img = np.reshape(img,[1,3]) # return the image with shaping that TF wants.
prediction = model.predict(img)
prediction
但在 .ipynb 文件的情况下,我只是收到有关此的警告:-
解决方法
你是resizing to wrong shape
。而不是240,240
img = cv2.resize(img,(240,240)) # resize image to match model's expected sizing
img = img.reshape(1,240,3) # return the image with shaping that TF wants.
使用224,224
img = cv2.resize(img,(224,224)) # resize image to match model's expected sizing
img = img.reshape(1,224,3) # return the image with shaping that TF wants.