Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Sat Dec 18 15:52:10 2021
+
+@author: riche
+"""
+
+import pandas as pd
+import numpy as np 
+from sklearn.preprocessing import MinMaxScaler
+from keras.models import load_model
+import gradio as gr 
+
+X_train = train.copy()
+y_train = X_train.pop('label')
+
+
+scale = MinMaxScaler()
+X_train = scale.fit_transform(X_train)
+
+model = load_model('digit_recognizer_modeldef.h5')
+
+def sketch_recognition(img):
+  # Implement sketch recognition model here...
+  # Return labels and confidences as dictionary
+    img = img.reshape((1, 784))
+    img = scale.transform(img.reshape(1, -1))
+    preds = model.predict(np.array(img).reshape((1, 28, 28, 1))).tolist()[0]
+    return {str(i): preds[i] for i in range(10)}
+
+interface = gr.Interface(fn=sketch_recognition, inputs="sketchpad", outputs=gr.outputs.Label()).launch(share=True)