nlpconnect / vit-gpt2-image-captioning

huggingface.co
Total runs: 85.2K
24-hour runs: 0
7-day runs: -12.2K
30-day runs: -25.6K
Model's Last Updated: February 27 2023
image-to-text

Introduction of vit-gpt2-image-captioning

Model Details of vit-gpt2-image-captioning

nlpconnect/vit-gpt2-image-captioning

This is an image captioning model trained by @ydshieh in flax this is pytorch version of this .

The Illustrated Image Captioning using transformers

Sample running code


from transformers import VisionEncoderDecoderModel, ViTImageProcessor, AutoTokenizer
import torch
from PIL import Image

model = VisionEncoderDecoderModel.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
feature_extractor = ViTImageProcessor.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
tokenizer = AutoTokenizer.from_pretrained("nlpconnect/vit-gpt2-image-captioning")

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)



max_length = 16
num_beams = 4
gen_kwargs = {"max_length": max_length, "num_beams": num_beams}
def predict_step(image_paths):
  images = []
  for image_path in image_paths:
    i_image = Image.open(image_path)
    if i_image.mode != "RGB":
      i_image = i_image.convert(mode="RGB")

    images.append(i_image)

  pixel_values = feature_extractor(images=images, return_tensors="pt").pixel_values
  pixel_values = pixel_values.to(device)

  output_ids = model.generate(pixel_values, **gen_kwargs)

  preds = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
  preds = [pred.strip() for pred in preds]
  return preds


predict_step(['doctor.e16ba4e4.jpg']) # ['a woman in a hospital bed with a woman in a hospital bed']

Sample running code using transformers pipeline


from transformers import pipeline

image_to_text = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")

image_to_text("https://ankur3107.github.io/assets/images/image-captioning-example.png")

# [{'generated_text': 'a soccer game with a player jumping to catch the ball '}]

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Runs of nlpconnect vit-gpt2-image-captioning on huggingface.co

85.2K
Total runs
0
24-hour runs
-1.4K
3-day runs
-12.2K
7-day runs
-25.6K
30-day runs

More Information About vit-gpt2-image-captioning huggingface.co Model

More vit-gpt2-image-captioning license Visit here:

https://choosealicense.com/licenses/apache-2.0

vit-gpt2-image-captioning huggingface.co

vit-gpt2-image-captioning huggingface.co is an AI model on huggingface.co that provides vit-gpt2-image-captioning's model effect (), which can be used instantly with this nlpconnect vit-gpt2-image-captioning model. huggingface.co supports a free trial of the vit-gpt2-image-captioning model, and also provides paid use of the vit-gpt2-image-captioning. Support call vit-gpt2-image-captioning model through api, including Node.js, Python, http.

vit-gpt2-image-captioning huggingface.co Url

https://huggingface.co/nlpconnect/vit-gpt2-image-captioning

nlpconnect vit-gpt2-image-captioning online free

vit-gpt2-image-captioning huggingface.co is an online trial and call api platform, which integrates vit-gpt2-image-captioning's modeling effects, including api services, and provides a free online trial of vit-gpt2-image-captioning, you can try vit-gpt2-image-captioning online for free by clicking the link below.

nlpconnect vit-gpt2-image-captioning online free url in huggingface.co:

https://huggingface.co/nlpconnect/vit-gpt2-image-captioning

vit-gpt2-image-captioning install

vit-gpt2-image-captioning is an open source model from GitHub that offers a free installation service, and any user can find vit-gpt2-image-captioning on GitHub to install. At the same time, huggingface.co provides the effect of vit-gpt2-image-captioning install, users can directly use vit-gpt2-image-captioning installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

vit-gpt2-image-captioning install url in huggingface.co:

https://huggingface.co/nlpconnect/vit-gpt2-image-captioning

Url of vit-gpt2-image-captioning

vit-gpt2-image-captioning huggingface.co Url

Provider of vit-gpt2-image-captioning huggingface.co

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