Full1

import skvideo.io
import skvideo.datasets
import tensorflow as tf
from tensorflow.keras.applications.resnet50 import ResNet50
from tensorflow.keras.applications.resnet50 import preprocess_input, decode_predictions

# enabling eager execution for easier explanation
tf.enable_eager_execution()

model = ResNet50(weights='imagenet')

reader = skvideo.io.FFmpegReader(skvideo.datasets.bigbuckbunny(),
                             inputdict={},
                             outputdict={})
def gen_frames():
    for frame in reader.nextFrame():
        yield frame

dataset = tf.data.Dataset.from_generator(gen_frames, tf.int64)

def preprocess(frames):
    x = tf.image.resize_bilinear(frames, [224, 224])
    x = preprocess_input(x)
    return x

dataset = dataset.batch(64).map(preprocess, 10).prefetch(1)

for value in dataset:
    print(decode_predictions(model.predict(value.numpy())))