inceptionv3.py

import matplotlib.pyplot as plt
import os, json
from glob import glob

import tensorflow.keras
import tensorflow as tf

from tensorflow.keras.applications import inception_v3, vgg16
from tensorflow.keras.preprocessing import image
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Dense, GlobalAveragePooling2D
from tensorflow.keras import backend as K
from tensorflow.keras.applications.imagenet_utils import preprocess_input, decode_predictions

import numpy as np
from IPython.display import Image

model = inception_v3.InceptionV3(weights='imagenet', include_top=True)

image_path = './test/'

model.summary()
len(model.layers)

img_path = os.path.join(image_path, 'image_here.jpg')   # change dis
img = image.load_img(img_path, target_size=(299,299))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = inception_v3.preprocess_input(x)
print('Input Image Shape: ', x.shape)

preds = model.predict(x)
print('Predicted: ', decode_predictions(preds))

Image(img_path)