|
from transformers import AutoFeatureExtractor, ResNetForImageClassification |
|
import torch |
|
from datasets import load_dataset |
|
|
|
dataset = load_dataset("huggingface/cats-image") |
|
image = dataset["test"]["image"][0] |
|
|
|
feature_extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50") |
|
model = ResNetForImageClassification.from_pretrained("microsoft/resnet-50") |
|
|
|
inputs = feature_extractor(image, return_tensors="pt") |
|
|
|
with torch.no_grad(): |
|
logits = model(**inputs).logits |
|
|
|
|
|
predicted_label = logits.argmax(-1).item() |
|
print(model.config.id2label[predicted_label]) |
|
|
|
import gradio as gr |
|
def segment(image): |
|
pass |
|
|
|
gr.Interface(fn=segment, inputs="image", outputs="image").launch() |