Upping space

app.py

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+import gradio as gr
+import tensorflow as tf
+import numpy as np
+import matplotlib.image as mpimg
+from tensorflow.keras import  models
+
+
+model = models.load_model('saved_model/my_model')
+UPPERCASE_ALFABET = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"]
+
+def predict(img):
+    image = mpimg.imread(img)
+    image = np.expand_dims(image, axis=0)  
+    image_tensor = tf.constant(image, dtype=tf.float32)
+    result = model.predict(image_tensor)[0]
+    return UPPERCASE_ALFABET[np.argmax(result)]
+
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(28, 28)),
+    outputs=gr.outputs.Label(num_top_classes=3),
+    title="Identificador de letras manuscritas",
+    description="Esse modelo tem a capacidade de identificar qual é a letra manuscrita.",
+    examples=["A.jpg","B.jpg","C.jpg","D.jpg","E.jpg"],
+).launch()

requirements.txt

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+pip
+gradio
+
+numpy
+tensorflow
+matplotlib
+tensorflow.keras