Added application

main.py

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+import tensorflow as tf
+from tensorflow.keras.models import load_model
+import gradio as gr
+import numpy as np
+import cv2
+
+model = load_model("model_1.h5")
+
+labels = ["zero","one","two","three","four","five","six","seven","eight","nine","ten","eleven","twelve","thrteen","fourteen","fifteen","sixteen","seventeen","eightteen","nineteen"]
+
+def predict(img):
+gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+resized = cv2.resize(gray, (64, 64))
+reshaped = resized.reshape(1, 64, 64, 1)
+out = model.predict(reshaped)
+cls = labels[out.argmax()]
+return cls
+
+ui = gr.Interface(
+fn=predict,
+inputs=gr.Image(type="numpy"),
+outputs=gr.Textbox()
+)

model_1.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cf6ba496976fbc39fc512ec182deef1ee742f16f804c567e60ccb15e6f617976
+size 9354040

requirements.txt

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+tensorflow
+gradio
+opencv-python
+numpy