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_01.h5') classnames = ['Pikachu','Raichu'] 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(2)} image = gr.inputs.Image(shape=(224, 224)) label = gr.outputs.Label(num_top_classes=2) article="
Made by Aditya Narendra with 🖤
" examples = ['battery.jpeg','cardboard.jpeg','paper.jpg','clothes.jpeg','metal.jpg','plastic.jpg','shoes.jpg'] gr.Interface(fn=predict_image, inputs=image, title="Garbage Classifier V3", description="This is a Garbage Classification Model Trained using MobileNetV2.Deployed to Hugging Faces using Gradio.",outputs=label,examples=examples,article=article,enable_queue=True,interpretation='default').launch(share="True")