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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('Exp33DIG.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') |