Spaces:
Running
on
Zero
Running
on
Zero
| import spaces | |
| import os | |
| import re | |
| import traceback | |
| import torch | |
| import gradio as gr | |
| import sys | |
| sys.path.append('./VideoLLaMA2') | |
| from videollama2 import model_init, mm_infer | |
| from videollama2.utils import disable_torch_init | |
| title_markdown = (""" | |
| <div style="display: flex; justify-content: center; align-items: center; text-align: center;"> | |
| <a href="https://github.com/DAMO-NLP-SG/VideoLLaMA2" style="margin-right: 20px; text-decoration: none; display: flex; align-items: center;"> | |
| <img src="https://s2.loli.net/2024/06/03/D3NeXHWy5az9tmT.png" alt="VideoLLaMA 2 🔥🚀🔥" style="max-width: 120px; height: auto;"> | |
| </a> | |
| <div> | |
| <h1 >VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs</h1> | |
| <h5 style="margin: 0;">If this demo please you, please give us a star ⭐ on Github or 💖 on this space.</h5> | |
| </div> | |
| </div> | |
| <div align="center"> | |
| <div style="display:flex; gap: 0.25rem; margin-top: 10px;" align="center"> | |
| <a href="https://github.com/DAMO-NLP-SG/VideoLLaMA2"><img src='https://img.shields.io/badge/Github-VideoLLaMA2-9C276A'></a> | |
| <a href="https://arxiv.org/pdf/2406.07476.pdf"><img src="https://img.shields.io/badge/Arxiv-2406.07476-AD1C18"></a> | |
| <a href="https://github.com/DAMO-NLP-SG/VideoLLaMA2/stargazers"><img src="https://img.shields.io/github/stars/DAMO-NLP-SG/VideoLLaMA2.svg?style=social"></a> | |
| </div> | |
| </div> | |
| """) | |
| block_css = """ | |
| #buttons button { | |
| min-width: min(120px,100%); | |
| color: #9C276A | |
| } | |
| """ | |
| tos_markdown = (""" | |
| ### Terms of use | |
| By using this service, users are required to agree to the following terms: | |
| The service is a research preview intended for non-commercial use only. It only provides limited safety measures and may generate offensive content. It must not be used for any illegal, harmful, violent, racist, or sexual purposes. The service may collect user dialogue data for future research. | |
| Please click the "Flag" button if you get any inappropriate answer! We will collect those to keep improving our moderator. | |
| For an optimal experience, please use desktop computers for this demo, as mobile devices may compromise its quality. | |
| """) | |
| learn_more_markdown = (""" | |
| ### License | |
| This project is released under the Apache 2.0 license as found in the LICENSE file. The service is a research preview intended for non-commercial use ONLY, subject to the model Licenses of LLaMA and Mistral, Terms of Use of the data generated by OpenAI, and Privacy Practices of ShareGPT. Please get in touch with us if you find any potential violations. | |
| """) | |
| plum_color = gr.themes.colors.Color( | |
| name='plum', | |
| c50='#F8E4EF', | |
| c100='#E9D0DE', | |
| c200='#DABCCD', | |
| c300='#CBA8BC', | |
| c400='#BC94AB', | |
| c500='#AD809A', | |
| c600='#9E6C89', | |
| c700='#8F5878', | |
| c800='#804467', | |
| c900='#713056', | |
| c950='#662647', | |
| ) | |
| class Chat: | |
| def __init__(self, model_path, load_8bit=False, load_4bit=False): | |
| disable_torch_init() | |
| self.model, self.processor, self.tokenizer = model_init(model_path, load_8bit=load_8bit, load_4bit=load_4bit) | |
| def generate(self, data: list, message, temperature, top_p, max_output_tokens): | |
| # TODO: support multiple turns of conversation. | |
| assert len(data) == 1 | |
| tensor, modal = data[0] | |
| response = mm_infer(tensor, message, self.model, self.tokenizer, modal=modal.strip('<>'), | |
| do_sample=True if temperature > 0.0 else False, | |
| temperature=temperature, | |
| top_p=top_p, | |
| max_new_tokens=max_output_tokens) | |
| return response | |
| def generate(image, video, message, chatbot, textbox_in, temperature, top_p, max_output_tokens, dtype=torch.float16): | |
| data = [] | |
| processor = handler.processor | |
| try: | |
| if image is not None: | |
| data.append((processor['image'](image).to(handler.model.device, dtype=dtype), '<image>')) | |
| elif video is not None: | |
| data.append((processor['video'](video).to(handler.model.device, dtype=dtype), '<video>')) | |
| elif image is None and video is None: | |
| data.append((None, '<text>')) | |
| else: | |
| raise NotImplementedError("Not support image and video at the same time") | |
| except Exception as e: | |
| traceback.print_exc() | |
| return gr.update(value=None, interactive=True), gr.update(value=None, interactive=True), message, chatbot | |
| assert len(message) % 2 == 0, "The message should be a pair of user and system message." | |
| show_images = "" | |
| if image is not None: | |
| show_images += f'<img src="./file={image}" style="display: inline-block;width: 250px;max-height: 400px;">' | |
| if video is not None: | |
| show_images += f'<video controls playsinline width="500" style="display: inline-block;" src="./file={video}"></video>' | |
| one_turn_chat = [textbox_in, None] | |
| # 1. first run case | |
| if len(chatbot) == 0: | |
| one_turn_chat[0] += "\n" + show_images | |
| # 2. not first run case | |
| else: | |
| # scanning the last image or video | |
| length = len(chatbot) | |
| for i in range(length - 1, -1, -1): | |
| previous_image = re.findall(r'<img src="./file=(.+?)"', chatbot[i][0]) | |
| previous_video = re.findall(r'<video controls playsinline width="500" style="display: inline-block;" src="./file=(.+?)"', chatbot[i][0]) | |
| if len(previous_image) > 0: | |
| previous_image = previous_image[-1] | |
| # 2.1 new image append or pure text input will start a new conversation | |
| if (video is not None) or (image is not None and os.path.basename(previous_image) != os.path.basename(image)): | |
| message.clear() | |
| one_turn_chat[0] += "\n" + show_images | |
| break | |
| elif len(previous_video) > 0: | |
| previous_video = previous_video[-1] | |
| # 2.2 new video append or pure text input will start a new conversation | |
| if image is not None or (video is not None and os.path.basename(previous_video) != os.path.basename(video)): | |
| message.clear() | |
| one_turn_chat[0] += "\n" + show_images | |
| break | |
| message.append({'role': 'user', 'content': textbox_in}) | |
| text_en_out = handler.generate(data, message, temperature=temperature, top_p=top_p, max_output_tokens=max_output_tokens) | |
| message.append({'role': 'assistant', 'content': text_en_out}) | |
| one_turn_chat[1] = text_en_out | |
| chatbot.append(one_turn_chat) | |
| return gr.update(value=image, interactive=True), gr.update(value=video, interactive=True), message, chatbot | |
| def regenerate(message, chatbot): | |
| message.pop(-1), message.pop(-1) | |
| chatbot.pop(-1) | |
| return message, chatbot | |
| def clear_history(message, chatbot): | |
| message.clear(), chatbot.clear() | |
| return (gr.update(value=None, interactive=True), | |
| gr.update(value=None, interactive=True), | |
| message, chatbot, | |
| gr.update(value=None, interactive=True)) | |
| # BUG of Zero Environment | |
| # 1. The environment is fixed to torch>=2.0,<=2.2, gradio>=4.x.x | |
| # 2. The operation or tensor which requires cuda are limited in those functions wrapped via spaces.GPU | |
| # 3. The function can't return tensor or other cuda objects. | |
| model_path = 'DAMO-NLP-SG/VideoLLaMA2.1-7B-16F' | |
| handler = Chat(model_path, load_8bit=False, load_4bit=True) | |
| textbox = gr.Textbox(show_label=False, placeholder="Enter text and press ENTER", container=False) | |
| theme = gr.themes.Default(primary_hue=plum_color) | |
| # theme.update_color("primary", plum_color.c500) | |
| theme.set(slider_color="#9C276A") | |
| theme.set(block_title_text_color="#9C276A") | |
| theme.set(block_label_text_color="#9C276A") | |
| theme.set(button_primary_text_color="#9C276A") | |
| # theme.set(button_secondary_text_color="*neutral_800") | |
| with gr.Blocks(title='VideoLLaMA 2 🔥🚀🔥', theme=theme, css=block_css) as demo: | |
| gr.Markdown(title_markdown) | |
| message = gr.State([]) | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| image = gr.Image(label="Input Image", type="filepath") | |
| video = gr.Video(label="Input Video") | |
| with gr.Accordion("Parameters", open=True) as parameter_row: | |
| # num_beams = gr.Slider( | |
| # minimum=1, | |
| # maximum=10, | |
| # value=1, | |
| # step=1, | |
| # interactive=True, | |
| # label="beam search numbers", | |
| # ) | |
| temperature = gr.Slider( | |
| minimum=0.1, | |
| maximum=1.0, | |
| value=0.2, | |
| step=0.1, | |
| interactive=True, | |
| label="Temperature", | |
| ) | |
| top_p = gr.Slider( | |
| minimum=0.0, | |
| maximum=1.0, | |
| value=0.7, | |
| step=0.1, | |
| interactive=True, | |
| label="Top P", | |
| ) | |
| max_output_tokens = gr.Slider( | |
| minimum=64, | |
| maximum=1024, | |
| value=512, | |
| step=64, | |
| interactive=True, | |
| label="Max output tokens", | |
| ) | |
| with gr.Column(scale=7): | |
| chatbot = gr.Chatbot(label="VideoLLaMA 2", bubble_full_width=True, height=750) | |
| with gr.Row(): | |
| with gr.Column(scale=8): | |
| textbox.render() | |
| with gr.Column(scale=1, min_width=50): | |
| submit_btn = gr.Button(value="Send", variant="primary", interactive=True) | |
| with gr.Row(elem_id="buttons") as button_row: | |
| upvote_btn = gr.Button(value="👍 Upvote", interactive=True) | |
| downvote_btn = gr.Button(value="👎 Downvote", interactive=True) | |
| # flag_btn = gr.Button(value="⚠️ Flag", interactive=True) | |
| # stop_btn = gr.Button(value="⏹️ Stop Generation", interactive=False) | |
| regenerate_btn = gr.Button(value="🔄 Regenerate", interactive=True) | |
| clear_btn = gr.Button(value="🗑️ Clear history", interactive=True) | |
| with gr.Row(): | |
| with gr.Column(): | |
| cur_dir = os.path.dirname(os.path.abspath(__file__)) | |
| gr.Examples( | |
| examples=[ | |
| [ | |
| f"{cur_dir}/examples/extreme_ironing.jpg", | |
| "What happens in this image?", | |
| ], | |
| [ | |
| f"{cur_dir}/examples/waterview.jpg", | |
| "What are the things I should be cautious about when I visit here?", | |
| ], | |
| [ | |
| f"{cur_dir}/examples/desert.jpg", | |
| "If there are factual errors in the questions, point it out; if not, proceed answering the question. What’s happening in the desert?", | |
| ], | |
| ], | |
| inputs=[image, textbox], | |
| ) | |
| with gr.Column(): | |
| gr.Examples( | |
| examples=[ | |
| [ | |
| f"{cur_dir}/examples/rap.mp4", | |
| "What happens in this video?", | |
| ], | |
| [ | |
| f"{cur_dir}/examples/demo2.mp4", | |
| "Do you think it's morning or night in this video? Why?", | |
| ], | |
| [ | |
| f"{cur_dir}/examples/demo3.mp4", | |
| "At the intersection, in which direction does the red car turn?", | |
| ], | |
| ], | |
| inputs=[video, textbox], | |
| ) | |
| gr.Markdown(tos_markdown) | |
| gr.Markdown(learn_more_markdown) | |
| submit_btn.click( | |
| generate, | |
| [image, video, message, chatbot, textbox, temperature, top_p, max_output_tokens], | |
| [image, video, message, chatbot]) | |
| regenerate_btn.click( | |
| regenerate, | |
| [message, chatbot], | |
| [message, chatbot]).then( | |
| generate, | |
| [image, video, message, chatbot, textbox, temperature, top_p, max_output_tokens], | |
| [image, video, message, chatbot]) | |
| clear_btn.click( | |
| clear_history, | |
| [message, chatbot], | |
| [image, video, message, chatbot, textbox]) | |
| demo.launch() | |