Create app.py

app.py

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+# TensorFlow and tf.keras
+import tensorflow as tf
+
+# Helper libraries
+import numpy as np
+import cv2
+import os
+import matplotlib.pyplot as plt
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import confusion_matrix, classification_report
+import h5py
+import gradio as gr
+
+#category
+
+cat = ['EIGHT', 'FIVE', 'FOUR', 'NINE', 'ONE', 'SEVEN', 'SIX', 'THREE', 'TWO', 'ZERO']
+
+def predict_image(img):
+  model=tf.keras.models.load_model('/content/drive/MyDrive/FYP/Exp32DIG.hdf5')
+  img_4d=img.reshape(-1,224,224,1)
+  prediction=model.predict(img_4d)[0]
+  return {cat[i]: float(prediction[i]) for i in range(10)}
+
+image = gr.inputs.Image(shape=(224,224))
+label = gr.outputs.Label(num_top_classes=10)
+
+gr.Interface(fn=predict_image, inputs=image, outputs=label, title="Sign Language Digit", allow_flagging="never").launch(debug='True')