Day #59 - Image Object Classification using Keras

This post is for basic image classification in Keras using VGG19. We leverage pre-trained models to detect objects in the image

	from keras.applications import VGG19
	from keras.applications import imagenet_utils
	from keras.preprocessing.image import img_to_array
	from keras.preprocessing.image import load_img
	import numpy as np
	input_shape = (224,224)
	preprocess = imagenet_utils.preprocess_input
	image = load_img("E:\RNotes\DL\man.png", target_size = input_shape)
	image = img_to_array(image)
	image = np.expand_dims(image,axis=0)
	image = preprocess(image)
	#model = VGG19(weights="imagenet")
	model = VGG19(weights="imagenet")
	preds = model.predict(image)
	p = imagenet_utils.decode_predictions(preds)
	print(p)
	#VGG19
	#Women
	#[[('n03770439', 'miniskirt', 0.47218892), ('n03594734', 'jean', 0.20757468), ('n02963159', 'cardigan', 0.022973826), ('n03450230', 'gown', 0.021934472), ('n03000247', 'chain_mail', 0.02097792)]]
	#man
	#[[('n03594734', 'jean', 0.31298622), ('n03630383', 'lab_coat', 0.26774961), ('n04456115', 'torch', 0.083450332), ('n04296562', 'stage', 0.04125011), ('n04370456', 'sweatshirt', 0.021016017)]]

view raw kerasobjectsreg.py hosted with ❤ by GitHub

Happy Learning!!!