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Running
on
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Running
on
Zero
import gradio as gr | |
from transformers import AutoProcessor, AutoModelForCausalLM | |
import spaces | |
from PIL import Image | |
import subprocess | |
subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True) | |
models = { | |
'gokaygokay/Florence-2-Flux-Large': AutoModelForCausalLM.from_pretrained('gokaygokay/Florence-2-Flux-Large', trust_remote_code=True).eval(), | |
'gokaygokay/Florence-2-Flux': AutoModelForCausalLM.from_pretrained('gokaygokay/Florence-2-Flux', trust_remote_code=True).eval(), | |
} | |
processors = { | |
'gokaygokay/Florence-2-Flux-Large': AutoProcessor.from_pretrained('gokaygokay/Florence-2-Flux-Large', trust_remote_code=True), | |
'gokaygokay/Florence-2-Flux': AutoProcessor.from_pretrained('gokaygokay/Florence-2-Flux', trust_remote_code=True), | |
} | |
title = """<h1 align="center">Florence-2 Captioner for Flux Prompts</h1> | |
<p><center> | |
<a href="https://huggingface.co/gokaygokay/Florence-2-Flux-Large" target="_blank">[Florence-2 Flux Large]</a> | |
<a href="https://huggingface.co/gokaygokay/Florence-2-Flux" target="_blank">[Florence-2 Flux Base]</a> | |
</center></p> | |
""" | |
def run_example(image, model_name='gokaygokay/Florence-2-Flux-Large'): | |
image = Image.fromarray(image) | |
task_prompt = "<DESCRIPTION>" | |
prompt = task_prompt + "Describe this image in great detail." | |
if image.mode != "RGB": | |
image = image.convert("RGB") | |
model = models[model_name] | |
processor = processors[model_name] | |
inputs = processor(text=prompt, images=image, return_tensors="pt") | |
generated_ids = model.generate( | |
input_ids=inputs["input_ids"], | |
pixel_values=inputs["pixel_values"], | |
max_new_tokens=1024, | |
num_beams=3, | |
repetition_penalty=1.10, | |
) | |
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0] | |
parsed_answer = processor.post_process_generation(generated_text, task=task_prompt, image_size=(image.width, image.height)) | |
return parsed_answer["<DESCRIPTION>"] | |
with gr.Blocks(theme='bethecloud/storj_theme') as demo: | |
gr.HTML(title) | |
with gr.Row(): | |
with gr.Column(): | |
input_img = gr.Image(label="Input Picture") | |
model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value='gokaygokay/Florence-2-Flux-Large') | |
submit_btn = gr.Button(value="Submit") | |
with gr.Column(): | |
output_text = gr.Textbox(label="Output Text") | |
gr.Examples( | |
[["image1.jpg"], | |
["image2.jpg"], | |
["image3.png"], | |
["image5.jpg"]], | |
inputs=[input_img, model_selector], | |
outputs=[output_text], | |
fn=run_example, | |
label='Try captioning on below examples', | |
cache_examples=True | |
) | |
submit_btn.click(run_example, [input_img, model_selector], [output_text]) | |
demo.launch(debug=True) |