| # TF for image classification model | |
| import tensorflow | |
| import numpy | |
| from PIL import Image | |
| model = tensorflow.saved_model.load('./') | |
| classes = [ "Healthy" , "Gray_Leaf_Spot" , "Blight" , "Common_Rust" , ] | |
| img = Image.open("image.jpg").convert('RGB') | |
| img = img.resize((300, 300 * img.size[1] // img.size[0]), Image.ANTIALIAS) | |
| inp_numpy = numpy.array(img)[None] | |
| inp = tensorflow.constant(inp_numpy, dtype='float32') | |
| class_scores = model(inp)[0].numpy() | |
| print("") | |
| print("class_scores", class_scores) | |
| print("Class : ", classes[class_scores.argmax()]) |