我遇到以下错误:ValueError:无法将字符串转换为float:'nonPdr',当我运行以下代码时:
model = Sequential()
model.add(Conv2D(input_shape=(605,700,3), filters=64, kernel_size=(3,3), padding="valid",activation="tanh"))
model.add(Flatten())
model.add(Dense(32, activation='tanh', input_dim=100))
model.add(Dense(1, activation='sigmoid'))
model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['accuracy'])
data, labels = ReadImages(TRAIN_DIR)
# Train the model, iterating on the data in batches of 32 samples
model.fit(np.array(data), np.array(labels), epochs=10, batch_size=32)
Detail:'nonPdr'是我的两个img类之一
更新我的readImg方法
def ReadImages(Path):
ImageList = list()
LabelList = list()
ImageCV = list()
# Get all subdirectories
FolderList = os.listdir(Path)
# Loop over each directory
for File in FolderList:
if(os.path.isdir(os.path.join(Path, File))):
for Image in os.listdir(os.path.join(Path, File)):
# Add the image path to the list
ImageList.append(os.path.join(Path, File) + os.path.sep + Image)
# Convert the path into a file
ImageCV.append(cv2.imread(os.path.join(Path, File) + os.path.sep + Image))
# Add a label for each image and remove the file extension
LabelList.append(os.path.splitext(File)[0])
else:
ImageList.append(os.path.join(Path, File))
ImageCV.append(cv2.imread(os.path.join(Path, File) + os.path.sep + Image))
# Add a label for each image and remove the file extension
LabelList.append(os.path.splitext(File)[0])
return ImageCV, LabelList
在ReadImages函数中,您正在创建字符串列表:
稍后当您使用ReadImages函数时,您将尝试将此字符串列表转换为numpy数组。此处:
可能的解决方案是将类名指定给数字:
当您的类为“nonPdr”时,0将附加到LabelList;如果您的类为“other\u class”,则1将附加到LabelList。你知道吗
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