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Running
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A10G
import argparse | |
import os | |
import random | |
import numpy as np | |
import torch | |
import torch.backends.cudnn as cudnn | |
import gradio as gr | |
from minigpt4.common.config import Config | |
from minigpt4.common.dist_utils import get_rank | |
from minigpt4.common.registry import registry | |
from minigpt4.conversation.conversation import Chat, CONV_VISION | |
# imports modules for registration | |
from minigpt4.datasets.builders import * | |
from minigpt4.models import * | |
from minigpt4.processors import * | |
from minigpt4.runners import * | |
from minigpt4.tasks import * | |
def parse_args(): | |
parser = argparse.ArgumentParser(description="Demo") | |
parser.add_argument("--cfg-path", type=str, default='eval_configs/minigpt4.yaml', help="path to configuration file.") | |
parser.add_argument( | |
"--options", | |
nargs="+", | |
help="override some settings in the used config, the key-value pair " | |
"in xxx=yyy format will be merged into config file (deprecate), " | |
"change to --cfg-options instead.", | |
) | |
args = parser.parse_args() | |
return args | |
def setup_seeds(config): | |
seed = config.run_cfg.seed + get_rank() | |
random.seed(seed) | |
np.random.seed(seed) | |
torch.manual_seed(seed) | |
cudnn.benchmark = False | |
cudnn.deterministic = True | |
# ======================================== | |
# Model Initialization | |
# ======================================== | |
SHARED_UI_WARNING = f'''### [NOTE] It is possible that you are waiting in a lengthy queue. | |
You can duplicate and use it with a paid private GPU. | |
<a class="duplicate-button" style="display:inline-block" target="_blank" href="https://huggingface.co/spaces/Vision-CAIR/minigpt4?duplicate=true"><img style="margin-top:0;margin-bottom:0" src="https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-xl-dark.svg" alt="Duplicate Space"></a> | |
Alternatively, you can also use the demo on our project page. | |
<a style="display:inline-block" href="https://minigpt-4.github.io"><img style="margin-top:0;margin-bottom:0" src="https://img.shields.io/badge/Project%20Page-online-brightgreen"></a> | |
''' | |
print('Initializing Chat') | |
cfg = Config(parse_args()) | |
model_config = cfg.model_cfg | |
model_cls = registry.get_model_class(model_config.arch) | |
model = model_cls.from_config(model_config).to('cuda:0') | |
vis_processor_cfg = cfg.datasets_cfg.cc_align.vis_processor.train | |
vis_processor = registry.get_processor_class(vis_processor_cfg.name).from_config(vis_processor_cfg) | |
chat = Chat(model, vis_processor) | |
print('Initialization Finished') | |
# ======================================== | |
# Gradio Setting | |
# ======================================== | |
def gradio_reset(chat_state, img_list): | |
if chat_state is not None: | |
chat_state.messages = [] | |
if img_list is not None: | |
img_list = [] | |
return None, gr.update(value=None, interactive=True), gr.update(placeholder='Please upload your image first', interactive=False), gr.update(value="Upload & Start Chat", interactive=True), chat_state, img_list | |
def upload_img(gr_img, text_input, chat_state): | |
if gr_img is None: | |
return None, None, gr.update(interactive=True), chat_state, None | |
chat_state = CONV_VISION.copy() | |
img_list = [] | |
llm_message = chat.upload_img(gr_img, chat_state, img_list) | |
return gr.update(interactive=False), gr.update(interactive=True, placeholder='Type and press Enter'), gr.update(value="Start Chatting", interactive=False), chat_state, img_list | |
def gradio_ask(user_message, chatbot, chat_state): | |
if len(user_message) == 0: | |
return gr.update(interactive=True, placeholder='Input should not be empty!'), chatbot, chat_state | |
chat.ask(user_message, chat_state) | |
chatbot = chatbot + [[user_message, None]] | |
return '', chatbot, chat_state | |
def gradio_answer(chatbot, chat_state, img_list, num_beams, temperature): | |
llm_message = chat.answer(conv=chat_state, img_list=img_list, max_new_tokens=300, num_beams=1, temperature=temperature, max_length=2000)[0] | |
chatbot[-1][1] = llm_message | |
return chatbot, chat_state, img_list | |
title = """<h1 align="center">Demo of MiniGPT-4</h1>""" | |
description = """<h3>This is the demo of MiniGPT-4. Upload your images and start chatting!</h3>""" | |
article = """<p><a href='https://minigpt-4.github.io'><img src='https://img.shields.io/badge/Project-Page-Green'></a></p><p><a href='https://github.com/Vision-CAIR/MiniGPT-4'><img src='https://img.shields.io/badge/Github-Code-blue'></a></p><p><a href='https://github.com/TsuTikgiau/blip2-llm/blob/release_prepare/MiniGPT_4.pdf'><img src='https://img.shields.io/badge/Paper-PDF-red'></a></p> | |
""" | |
#TODO show examples below | |
with gr.Blocks() as demo: | |
gr.Markdown(title) | |
gr.Markdown(SHARED_UI_WARNING) | |
gr.Markdown(description) | |
gr.Markdown(article) | |
with gr.Row(): | |
with gr.Column(scale=0.5): | |
image = gr.Image(type="pil") | |
upload_button = gr.Button(value="Upload & Start Chat", interactive=True, variant="primary") | |
clear = gr.Button("Restart") | |
num_beams = gr.Slider( | |
minimum=1, | |
maximum=5, | |
value=1, | |
step=1, | |
interactive=True, | |
label="beam search numbers)", | |
) | |
temperature = gr.Slider( | |
minimum=0.1, | |
maximum=2.0, | |
value=1.0, | |
step=0.1, | |
interactive=True, | |
label="Temperature", | |
) | |
with gr.Column(): | |
chat_state = gr.State() | |
img_list = gr.State() | |
chatbot = gr.Chatbot(label='MiniGPT-4') | |
text_input = gr.Textbox(label='User', placeholder='Please upload your image first', interactive=False) | |
upload_button.click(upload_img, [image, text_input, chat_state], [image, text_input, upload_button, chat_state, img_list]) | |
text_input.submit(gradio_ask, [text_input, chatbot, chat_state], [text_input, chatbot, chat_state]).then( | |
gradio_answer, [chatbot, chat_state, img_list, num_beams, temperature], [chatbot, chat_state, img_list] | |
) | |
clear.click(gradio_reset, [chat_state, img_list], [chatbot, image, text_input, upload_button, chat_state, img_list], queue=False) | |
demo.launch(enable_queue=True) |