import gradio as gr | |
import tensorflow as tf | |
import numpy as np | |
from PIL import Image | |
import tensorflow.keras as keras | |
from tensorflow.keras.models import load_model | |
# load model | |
model = load_model('model_15.h5') | |
classnames = ['Pikachu','Raichu','Pichu'] | |
def predict_image(img): | |
img_4d=img.reshape(-1,224, 224,3) | |
prediction=model.predict(img_4d)[0] | |
return {classnames[i]: float(prediction[i]) for i in range(3)} | |
image = gr.inputs.Image(shape=(224, 224)) | |
label = gr.outputs.Label(num_top_classes=3) | |
gr.Interface(fn=predict_image, inputs=image, title="Garbage Classifier V3", | |
description="ThiFaces using Gradio.",outputs=label,enable_queue=True,interpretation='default').launch() |