Spaces:
Build error
Build error
import gradio as gr | |
import tensorflow as tf | |
import numpy as np | |
num_classes = 200 | |
IMG_HEIGHT = 300 | |
IMG_WIDTH = 300 | |
with open("classlabel.txt", 'r') as file: | |
CLASS_LABEL = [x.strip() for x in file.readlines()] | |
def normalize_image(img): | |
img = tf.cast(img, tf.float32) / 255. | |
img = tf.image.resize(img, (IMG_HEIGHT, IMG_WIDTH), method='bilinear') | |
return img | |
def predict_top_classes(img, num_top_classes=5): | |
img = img.convert('RGB') | |
img_data = _normalize_img(img) | |
x = np.array(img_data) | |
x = np.expand_dims(x, axis=0) | |
temp = model.predict(x) | |
idx = np.argsort(np.squeeze(temp))[::-1] | |
top5_value = np.asarray([temp[0][i] for i in idx[0:5]]) | |
top5_idx = idx[0:5] | |
return {CLASS_LABEL[i]:str(v) for i,v in zip(top5_idx,top5_value)} | |
model = tf.keras.models.load_model("Xception.h5") | |
interface = gr.Interface(predict_top_classes, gr.inputs.Image(type='pil'), outputs='label', args={'num_top_classes': 5}) | |
interface.launch() | |