from PIL import Image
image = Image.open("airplane.jpg") # Choose an image of your choice and make sure it is in the same folder as this python script.
import tensorflow as tf
from transformers import AutoImageProcessor, TFResNetForImageClassification
# Load the model and image processor
model = TFResNetForImageClassification.from_pretrained("microsoft/resnet-50")
image_processor = AutoImageProcessor.from_pretrained("microsoft/resnet-50")
# Run Inference
inputs = image_processor(image, return_tensors="tf")
@tf.function
def predict():
return model(**inputs)
logits = predict().logits
predicted_label = int(tf.math.argmax(logits, axis=-1))
print(model.config.id2label[predicted_label])Sample Output
plane, carpenter's plane, woodworking plane