CasualTomes's picture
Update app.py
4579668 verified
raw
history blame contribute delete
852 Bytes
import gradio as gr
import tensorflow as tf
from tensorflow.keras.models import load_model
import numpy as np
class_names = ["bird", "cat", "deer", "dog"]
#CloudDeploymentTest/
model = load_model("model.keras")
def classify(input_img):
# We need to "normalize" the input.
# Input pixels are between 0 and 255,
# but neural net expects values 0 to 1.
input_img = np.array(input_img) / 255
# Add a batch dimension of size 1.
input_img = np.array([input_img])
# Run our image through the model.
prediction = model.predict(input_img)
# Remove batch dimension from output.
prediction = prediction[0]
# Turn softmax output into index.
prediction = np.argmax(prediction)
# Turn index into class name
return class_names[prediction]
demo = gr.Interface(classify, gr.Image(), "text")
demo.launch()