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import gradio as gr | |
from huggingface_hub import from_pretrained_keras | |
from tensorflow.keras.preprocessing.image import load_img | |
from tensorflow.keras.preprocessing.image import img_to_array | |
from tensorflow.keras.preprocessing import image | |
import numpy as np | |
model = from_pretrained_keras("yusyel/clothing") | |
class_names=["dress", | |
"hat", | |
"longsleee", | |
"outwear", | |
"pants", | |
"shirt", | |
"shoes", | |
"shorts", | |
"skirt", | |
"t-shirt"] | |
def preprocess_image(img): | |
img = load_img(img, target_size=(299, 299, 3)) | |
img = image.img_to_array(img) | |
img = np.expand_dims(img, axis=0) | |
img /= 255.0 | |
print(img.shape) | |
return img | |
def predict(img): | |
img = preprocess_image(img) | |
pred = model.predict(img) | |
pred = np.squeeze(np.exp(pred)/np.sum(np.exp(pred))).astype(float) | |
print(dict(zip(class_names, pred))) | |
return dict(zip(class_names, pred)) | |
with gr.Interface( | |
fn=predict, | |
inputs=[gr.inputs.Image(type="filepath")], | |
outputs=gr.outputs.Label(), | |
examples=[ | |
["./img/dress.jpg"], | |
["./img/hat.jpg"], | |
["./img/longsleeve.jpg"], | |
["./img/outwear.jpg"], | |
["./img/pants.jpg"], | |
["./img/shirt.jpg"], | |
["./img/shoes.jpg"], | |
["./img/short.jpg"], | |
["./img/skirt.jpg"], | |
["./img/t-shirt.jpg"], | |
], | |
title="Fashion Classification") as demo: | |
gr.Markdown("# This Demo For Free Machine Learning Zoomcamp", elem_classes=['center']) | |
gr.Markdown("Course github Links [github](https://github.com/DataTalksClub/machine-learning-zoomcamp)", | |
elem_classes=['center', 'small-big']) | |
demo.launch(server_name="0.0.0.0", server_port=7860) | |