Commit 661c74f3 authored by mihaivanea's avatar mihaivanea
Browse files

Started learning about resnet50.

parent e35890fa
import numpy as np
from keras.applications.resnet50 import ResNet50
from keras.preprocessing import image
from keras.applications.resnet50 import preprocess_input, decode_predictions
model = ResNet50(weights='imagenet')
img_path = "./tiger.jpg"
img = image.load_img(img_path, target_size=(224,224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
#decode the output into (class, description, probability)
preds = model.predict(x)
print("Predicted:", str(decode_predictions(preds, top=3)[0]))
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