Create app.py

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)