File size: 1,085 Bytes
756261a 0b38715 107902e 756261a 0b38715 107902e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 |
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "-1" # Disable GPU usage
import gradio as gr
import tensorflow as tf
from tensorflow.keras.preprocessing import image
import numpy as np
from transformers import pipeline
# Load image classification model from Hugging Face
model = pipeline("image-classification", model="icputrd/gelderman_decomposition_classification/head/xception_070523")
def classify_image(img):
# Preprocess the image
img = img.resize((299, 299)) # Resize to the input shape of Xception
img_array = image.img_to_array(img) # Convert image to array
img_array = np.expand_dims(img_array, axis=0) # Add batch dimension
img_array /= 255.0 # Normalize the image
# Make prediction
predictions = model.predict(img_array)
predicted_class = np.argmax(predictions, axis=-1)[0] # Get the predicted class index
return str(predicted_class) # Return the class index as a string
# Gradio interface for image classification
demo = gr.Interface(fn=classify_image, inputs=gr.inputs.Image(type="pil"), outputs="label")
demo.launch()
|