knnExample / app.py
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Create app.py
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import gradio as gr
from joblib import load
from skimage.transform import resize
from skimage.color import rgb2gray
import numpy as np
classifier = load('knn_classifier.joblib')
def predict_image(image):
if len(image.shape) == 3:
image = rgb2gray(image)
image = resize(image, (8,8),anti_aliasing=True, mode='reflect') #Redimensionamiento
image = (image * 255).astype(np.uint8)
#image = np.array(image, dtype = np.float64)
image = np.invert(image)
image = image.reshape(1,-1)
prediction = classifier.predict(image)
return prediction[0]
iface = gr.Interface(
fn = predict_image,
inputs = "image",
outputs = "text"
)
iface.launch(debug=True)