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Runtime error
| from turtle import title | |
| from transformers import pipeline | |
| import numpy as np | |
| from PIL import Image | |
| import gradio as gr | |
| #model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M") | |
| #tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M") | |
| #tokenizer.src_lang = "en" | |
| #encodedText = tokenizer(labels_text, return_tensors="pt") | |
| #generatedTokens = model.generate(**encodedText, forced_bos_token_id=tokenizer.get_lang_id("ru")) | |
| #return tokenizer.batch_decode(generatedTokens, skip_special_tokens=True)[0] | |
| pipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32") | |
| images="dog.jpg" | |
| def shot(image, labels_text): | |
| PIL_image = Image.fromarray(np.uint8(image)).convert('RGB') | |
| labels = labels_text.split(",") | |
| # Translate | |
| res = pipe(images=PIL_image, | |
| candidate_labels=labels, | |
| hypothesis_template= "This is a photo of a {}") | |
| return {dic["label"]: dic["score"] for dic in res} | |
| iface = gr.Interface(shot, | |
| ["image", "text"], | |
| "label", | |
| examples=[["dog.jpg", "dog,cat,bird"]], | |
| description="Add a picture and a list of labels separated by commas", | |
| title="Zero-shot Image Classification") | |
| iface.launch() |