【发布时间】:2021-04-02 21:30:03
【问题描述】:
我正在训练一个分类器,我确保所有图片都是 jpg,但仍然会发生此错误: InvalidArgumentError:未知的图像文件格式。需要 JPEG、PNG、GIF、BMP 之一。 [[{{node decode_image/DecodeImage}}]] [[IteratorGetNext]] [Op:__inference_train_function_1481]
我尝试在较小的数据集上进行训练,而且它们都是 jpg 并且没有问题
这是代码:
import numpy as np
import tensorflow as tf
from tensorflow import keras
dataset = keras.preprocessing.image_dataset_from_directory(
'/content/drive/MyDrive/fi_dataset/train', batch_size=64, image_size=(200, 200))
dense = keras.layers.Dense(units=16)
inputs = keras.Input(shape=(None, None, 3))
from tensorflow.keras import layers
x = CenterCrop(height=150, width=150)(inputs)
x = Rescaling(scale=1.0 / 255)(x)
x = layers.Conv2D(filters=32, kernel_size=(3, 3), activation="relu")(x)
x = layers.MaxPooling2D(pool_size=(3, 3))(x)
x = layers.Conv2D(filters=32, kernel_size=(3, 3), activation="relu")(x)
x = layers.MaxPooling2D(pool_size=(3, 3))(x)
x = layers.Conv2D(filters=32, kernel_size=(3, 3), activation="relu")(x)
x = layers.GlobalAveragePooling2D()(x)
num_classes = 1
outputs = layers.Dense(num_classes, activation="sigmoid")(x)
model = keras.Model(inputs=inputs, outputs=outputs)
data = np.random.randint(0, 256, size=(64, 200, 200, 3)).astype("float32")
processed_data = model(data)
model.compile(optimizer='adam',
loss='binary_crossentropy',
metrics=[keras.metrics.binary_accuracy],)
history=model.fit(dataset, epochs=10)
【问题讨论】:
标签: python image tensorflow keras google-colaboratory