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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) |