# create image data augmentation generator #Loading the image and coverting into Byte from numpy import expand_dimsįrom import load_imgįrom import img_to_arrayįrom import ImageDataGenerator iterator = imageDataGenerator_obj.flow(sam, batch_size=1)Ībove all, Here is the complete code from each step. Img_array= Image.open(BytesIO(uploaded))įor instance, we have taken the sample image "lamborghini_660_140220101539.jpg", you may change at your convenience. #Loading the image and converting into Byte Hence please change the code if you are doing it locally. Image loading and conversion into the array. Let’s implement the data argumentation with it. Step by step Implementation of brightness_range Keras – This will darken the image in this range. In the above syntax example, We have used the brightness_range=. And if you go above to 1 ( value) it will start brightening the image. If you go down to 1 it will start darkening the image. There is a big difference in the parameter of Tensorflow brightness_range with this API. from import ImageDataGeneratorĭatagen = ImageDataGenerator(brightness_range=) Let’s see the implementation of brightness_range in core Keras API.
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