jiayev / gpt4v-image-captioner

GPT4V-Image-Captioner / GPT4V图像打标器

中文版说明

We now have sd-webui-GPT4V-Image-Captioner for SD WebUI

This is a multifunctional image processing toolbox built with Gradio, capable of tagging images using the GPT-4-vision or Claude 3 API, the cogVLM model, Qwen-VL(Alibaba Cloud), the Moondream model.

Key features include:

• One-click installation and use
• Single image and multi-image batch tagging
• Choice of online GPT4V or Claude 3 or Qwen-VL(Alibaba Cloud) & local CogVLM and Moondream models
• Visual tag analysis and processing
• Image pre-compression
• Keyword filtering and watermark image recognition

Developers: Jiaye, LEOSAM是只兔狲, SleeeepyZhou, Fok, GPT4. Welcome everyone to add more new features to this project.

Please note that the Claude 3 feature is not finished yet.

To use Claude 3, simply replace the API key and URL with the Claude 3 API key and URL (/v1/messages), and changing the model name to "claude-3-opus" (or sonnet).

Installation and Startup Guide

Windows (If the automatic installation fails, please refer to the Manual Installation Instructions)

1. Open Command Prompt as administrator and navigate to the directory where you want to clone the repository.
2. Clone the repository using the following command:

   git clone https://github.com/jiayev/GPT4V-Image-Captioner
   

3. Double-click install_windows.bat to run and install all necessary dependencies.
4. After the installation is complete, you can launch the GPT4V-Image-Captioner by double-clicking start_windows.bat.
5. Hold down Ctrl and click on the URL in the terminal (or copy the URL to your browser), which will open the Gradio app interface in your default browser.
6. Enter the official OpenAI or third-party GPT-4V API Key and API Url at the top of the interface. After setting the image address, you can start tagging the image.

Linux / macOS

1. Open a terminal and navigate to the directory where you want to clone the repository.
2. Clone the repository using the following command:

   git clone https://github.com/jiayev/GPT4V-Image-Captioner
   

3. Navigate to the cloned directory:

   cd GPT4V-Image-Captioner
   

4. Make the install and start scripts executable with the following command:

   chmod +x install_linux_mac.sh; chmod +x start_linux_mac.sh
   

5. Execute the install script:

   ./install_linux_mac.sh
   

6. Launch the GPT4V-Image-Captioner in the terminal by executing the launch script:

   ./start_linux_mac.sh
   

7. Copy the URL displayed in the terminal and open it in your browser to access the Gradio app interface.
8. Enter the official OpenAI or third-party GPT-4V API Key and API Url at the top of the interface. After setting the image address, you can start tagging the image.

Windows Manual Installation Instructions

1. Open the Command Prompt by pressing Win + R, typing cmd, and then pressing Enter.

2. Clone the repository to your local machine using the following command:

   git clone https://github.com/jiayev/GPT4V-Image-Captioner
   

3. Once cloning is complete, navigate to the cloned directory:

   cd GPT4V-Image-Captioner
   

4. Before installing any dependencies, make sure that Python is installed on your system. Check for Python's presence by typing the following command and pressing Enter in the Command Prompt:

   python --version
   

   If Python is not installed, you will get an error message. In that case, please visit the Python official download page and follow the instructions to install it.

5. Create a virtual environment named myenv to avoid contaminating the global Python environment:

   python -m venv myenv
   

6. Activate the virtual environment you just created:

   myenv\Scripts\activate
   

7. Update pip to date:

   python -m pip install --upgrade pip
   

8. Install libraries within the virtual environment:

   pip install scipy networkx wordcloud matplotlib Pillow tqdm gradio requests
   

9. After completing the steps above, you can start GPT4V-Image-Captioner by double-clicking the start_windows.bat file.

gpt4v-image-captioner's Issues

Clarify readme on Key requirements

At multiple points in the top-level README.md instructions, it says,

"Enter the official OpenAI or third-party GPT-4V API Key and API Url at the top of the interface."

I was put off using this captioner because I thought I had to pay for an API key from those places.

Someone told me I can just use CogVLM instead?
If that is true, would you please update the readme in those sections, to add, ( Enter key .... If using those APIs) ?

单个图形打标不生成txt文件

批量打标生成txt文件，单个打标不生产

软件报错无法使用

错误日志指出在运行 Gradio 应用时遇到了一个 Unicode 编码问题。这个问题通常发生在尝试通过网络连接发送非ASCII字符时，如果编码设置不正确，就可能导致这个错误。

这里是你遇到错误的相关代码片段：

File "C:\Program Files\Python310\lib\http\client.py", line 1255, in putheader
values[i] = one_value.encode('latin-1')
UnicodeEncodeError: 'latin-1' codec can't encode characters in position 8-11: ordinal not in range(256)
在 Python 的 http.client 库中，putheader 方法尝试将请求头的值编码为 'latin-1'，但是当遇到无法用 'latin-1' 编码的字符时，就会报错。

要解决这个问题，你可以尝试以下步骤：

更新你的请求头编码：确保你的请求头使用 'utf-8' 编码。如果你在代码中手动设置了请求头，应该确保它们的编码是 'utf-8'。

使用 Requests 库：如果你正在使用 requests 库来发送 HTTP 请求，它会自动处理编码问题，通常不需要手动设置编码。

检查 Gradio 应用代码：查看你的 Gradio 应用代码，特别是 gpt-caption.py 和 Api_Utils.py 文件中与发送请求相关的部分，确保没有手动设置错误的编码。

更新依赖：确保你的环境中安装的 gradio，requests，和 urllib3 库都是最新版本。

联系 Gradio 支持：如果问题依然存在，考虑向 Gradio 的维护团队报告这个问题，因为这可能是一个库的bug。

临时解决方案：如果你需要临时绕过这个问题，可以尝试升级或降级 Python 的版本，或者在虚拟环境中重新安装所有相关的库。

检查网络连接：由于你提到网页解析没有成功，确保你的网络连接是稳定的，并且没有任何防火墙或代理阻止了你的连接。

最后，关于日志中提到的 "Running on local URL: http://127.0.0.1:8848"，这表明你的 Gradio 应用正在本地服务器上运行，并且可以通过这个地址访问。如果你想要创建一个公共链接，需要在启动 Gradio 应用时设置 share=True 参数。

如果自己用huggingface_cli 下载的CogVLM应该怎样在GIC文件夹里面配置呢？

大佬们，小弟远程链接国内的机器，用了GPT4V-Image-Captioner(GIC)里面自带default方法下载CogVLM但报错；然后用CN+魔法的方法下载，但手中电脑和国内机子的网络中断而经常看不到进度，不确定国内机子下载情况，所以想直接用hugging_cli下载(因为有resume download功能)，想问问如果我下载了 CogVLM, 应该把哪些文件放去GIC的哪些位置呢？
谢谢各位有缘人 ღ( ´･ᴗ･` )比心

Failed to parse the API response: Expecting value: line 1 column 1 (char 0)

Failed to parse the API response: Expecting value: line 1 column 1 (char 0)
<!doctype html><title>New API</title><script defer="defer" src="/static/js/main.630603bf.js"></script>You need to enable JavaScript to run this app.

add Llama3 and Claude

Would be amazing to add add Llama3 and Claude local models when available. Chatgpt api works great for me but a little pricy. Runs 0.07 dollars a caption. Ideally it would be 1/10th of that. Or local

HTTP Error: 404 Client Error: Not Found for url

I installed on Ubuntu 22.04 and I get this when I try to caption an image:
HTTP Error: 401 Client Error: Unauthorized for url: https://api.openai.com/v1/chat/completions

I obtained an api key from https://platform.openai.com/api-keys and pasted it into the first box "API Key" in the GUI but it still doesn't work. Is this the correct location to obtain an API key?
Still getting:
HTTP Error: 404 Client Error: Not Found for url: https://api.openai.com/v1/chat/completions

can you clarify the key/url setup?

Cache folder loacation change

Is there a way to change the cache folder location?
I am making my first trials with this nice tool and it seems the download of models to the cache folder on C causes issues.
I am not 100% as my system is so slow right now that I can't really use the any Windows menus.
The issue seems to be though that Defender directly jumps on the model files and even though I have a Nvme SSD as system drive it occupies it to 100% and makes the system almost unusable. I assume that the scan of model files is just screwed as the reading/writing performance is nowhere near the max, and the download of other large files to C is not making such a hassle.

Thanks.

使用单图caption，报错TypeError: gradio.data_classes.FileData() argument after ** must be a mapping, not str

Running on local URL: http://0.0.0.0:8081

To create a public link, set share=True in launch().
Traceback (most recent call last):
File "/data/miniconda3/envs/env-3.10-comfyui/lib/python3.10/site-packages/gradio/routes.py", line 732, in predict
output = await route_utils.call_process_api(
File "/data/miniconda3/envs/env-3.10-comfyui/lib/python3.10/site-packages/gradio/route_utils.py", line 276, in call_process_api
output = await app.get_blocks().process_api(
File "/data/miniconda3/envs/env-3.10-comfyui/lib/python3.10/site-packages/gradio/blocks.py", line 1924, in process_api
inputs = await self.preprocess_data(
File "/data/miniconda3/envs/env-3.10-comfyui/lib/python3.10/site-packages/gradio/blocks.py", line 1653, in preprocess_data
inputs_cached = block.data_model(**inputs_cached) # type: ignore
TypeError: gradio.data_classes.FileData() argument after ** must be a mapping, not str
Traceback (most recent call last):
File "/data/miniconda3/envs/env-3.10-comfyui/lib/python3.10/site-packages/gradio/routes.py", line 732, in predict
output = await route_utils.call_process_api(
File "/data/miniconda3/envs/env-3.10-comfyui/lib/python3.10/site-packages/gradio/route_utils.py", line 276, in call_process_api
output = await app.get_blocks().process_api(
File "/data/miniconda3/envs/env-3.10-comfyui/lib/python3.10/site-packages/gradio/blocks.py", line 1924, in process_api
inputs = await self.preprocess_data(
File "/data/miniconda3/envs/env-3.10-comfyui/lib/python3.10/site-packages/gradio/blocks.py", line 1653, in preprocess_data
inputs_cached = block.data_model(**inputs_cached) # type: ignore
TypeError: gradio.data_classes.FileData() argument after ** must be a mapping, not str

系统信息
gradio 4.36.1
gradio_client 1.0.1

Crashes when trying to use cog-vqa

I downloaded and installed the cog-vqa and cog-chat and it seems to load fine, but after hitting the "Process Tags" button I get this error:
Traceback (most recent call last):
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\gradio\queueing.py", line 495, in call_prediction
output = await route_utils.call_process_api(
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
output = await app.get_blocks().process_api(
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\gradio\blocks.py", line 1561, in process_api
result = await self.call_function(
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\gradio\blocks.py", line 1179, in call_function
prediction = await anyio.to_thread.run_sync(
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\anyio_backends_asyncio.py", line 2134, in run_sync_in_worker_thread
return await future
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\anyio_backends_asyncio.py", line 851, in run
result = context.run(func, *args)
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\gradio\utils.py", line 695, in wrapper
response = f(*args, **kwargs)
File "E:\GPT4V-Image-Captioner\lib\Tag_Processor.py", line 205, in process_tags
wordcloud_path = generate_wordcloud(folder_path, top)
File "E:\GPT4V-Image-Captioner\lib\Tag_Processor.py", line 149, in generate_wordcloud
wordcloud.generate_from_frequencies(dict(tag_counts))
File "E:\GPT4V-Image-Captioner\myenv\lib\site-packages\wordcloud\wordcloud.py", line 410, in generate_from_frequencies
raise ValueError("We need at least 1 word to plot a word cloud, "
ValueError: We need at least 1 word to plot a word cloud, got 0.

Llava-1.6 Support

Thank you for creating this project.

I managed to run it with moondream and will try CogVLM, but afaik Llava-1.6 (trained on Vicuna) is even better.

Is it already possible to run Llava-1.6 within your Captioner?
If it is, please tell us how.

If not please be so kind and add Llava-1.6 support.
https://github.com/camenduru/LLaVA

Thanks a lot!

使用VQA的时候，经常出现 Timeout Error: HTTPConnectionPool(host='127.0.0.1', port=8000): Read timed out. (read timeout=300)

Timeout Error: HTTPConnectionPool(host='127.0.0.1', port=8000): Read timed out. (read timeout=300)
请问这个问题怎么解决啊？

OOps: Something Else: HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded

Resizing images to below 1024px seems to fix the max retries error (429). I resized by 0.5x and now note getting errored txt files, but the speed to about 90 secs per image

OOps: Something Else: HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded with url: /v1/chat/completions (Caused by ResponseError('too many 429 error responses'))

Feature Request - Allow us to choose default model

Hello!

I would like the ability to choose the default model that would be used for each session. ATM I have to manually switch to the cog model I need instead of the default GPT which wastes time.

无法安装CogVLM

'HF_HOME' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'et' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'0' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
安装依赖
'BLE_PIP_VERSION_CHECK' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'ACHE_DIR' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'X_URL' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'orch...' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'l' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
Use default
'lling' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'l' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'VEL' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
'install' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
命令语法不正确。

question

any options or intentions to work offline with a model ?

请问如何切换到 Qwen-VL 模型

如题，紫薯布丁

标签管理页面 Top N 标签传参是浮点型

标签管理页面 Top N 标签传参是浮点型，在代码中会报不是integer。

ResponseError('too many 429 error responses')

想着Q群和B站问都不太方便，就在这边提issue了，但不知道为啥他把我的原文翻译成英文了 不好意思……
Brief summary: After about 120 marks were made in the initial stage, the marking speed plummeted to 3-5 minutes per mark, and there was a high probability of the following errors:
OOps: Something Else: HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded with url: /v1/chat/completions (Caused by ResponseError('too many 429 error responses'))
I looked it up, and according to the article and the link (https://zhuanlan.zhihu.com/p/626593017), it seems that this can be circumvented by extending the interval between two requests, or exponential backoff, etc., and I do get a much faster response time when reversing a single image than when processing it in batches, and even if something goes wrong, I can get a quick result by closing and restarting the code.
I don't know python, but I think the problem is that the batch doesn't have a wait time, or satisfies the ability to wait for a forced restart, and I don't seem to see the option in the code to wait on request.

Of course, the problem can also be with the provider of my APIkey.
能得到答案的话就再好不过了，感谢大佬……

切换Cog-vqa模型后进入不了Cog-vqa对应的webui

You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
INFO: 127.0.0.1:44106 - "POST /v1/Cog-vqa HTTP/1.1" 200 OK
INFO: 10.3.91.48:52035 - "GET / HTTP/1.1" 404 Not Found

运行错误

请按任意键继续. . . Traceback (most recent call last):
File "E:\GPT4V-Image-Captioner-main\gpt-caption.py", line 27, in
import Translator
File "E:\GPT4V-Image-Captioner-main\Translator.py", line 55
{"role": "user", "content": f"����һ��Ӣ����ר�ң���ֱ�ӷ���'{text}'���п��ܵ��������ķ�����������Զ��ż��."}
^
SyntaxError: (unicode error) 'utf-8' codec can't decode byte 0xc4 in position 0: invalid continuation byte

Timeout Error: HTTPConnectionPool(host='127.0.0.1', port=8000): Read timed out. (read timeout=60) local COG

works fine if i do 1 image but when batch folder- this happens. How to fix it? not useing API but local cog model

希望能加入gemini模型

希望能加入gemini模型，没有gpt4api~~

[feature] 集成图片裁剪功能

大佬们好，我就用中文了...
很喜欢这个项目，打标方便了不止一点半点，真的很酷，非常感谢你们！

图片处理功能里已经有压缩功能了，但在处理训练集时，常常伴随裁剪。
请问有没有考虑集成birme的功能呢？
我看github上也有一个brime的项目。
https://github.com/livelifebythecode/birme-sd-variant

谢谢！

remote use on LAN?

Hi, can gradio be started with --listen so that it can be used on another computer on the same network?

HTTPSConnectionPool(host='api.openai.com', port=443

OOps: Something Else: HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded with url: //v1/chat/completions (Caused by ResponseError('too many 429 error responses'))

Api key already paste but still errro

Possible Integration?

I found a very useful tagging app which if integrated with GPT4V-Image-Captioner would make it the best data labeling solution for Stable Diffusion fine tuning. GPT4V-Image-Captioner would help populate the categories based on the target images and then use DatasetTag to further organize each captioning in an organize manner.
https://github.com/BinaryAlley/DatasetTag

xFormers can't load C++/CUDA extensions. xFormers was built for: PyTorch 2.1.1+cu121 with CUDA 1201 (you have 2.1.1+cpu)

I followed the installation method using the install_windows.bat for windows 11, then start_windows.bat and installed the missing dependencies using as seen in the image below.

Error message:

configuration_cogagent.py: 100%|██████████████████████████████████████████████████████████| 1.80k/1.80k [00:00<?, ?B/s]
.gitattributes: 100%|█████████████████████████████████████████████████████████████| 1.52k/1.52k [00:00<00:00, 1.30MB/s]
README.md: 100%|██████████████████████████████████████████████████████████████████████████| 7.46k/7.46k [00:00<?, ?B/s]
generation_config.json: 100%|█████████████████████████████████████████████████████████| 137/137 [00:00<00:00, 91.2kB/s]
config.json: 100%|████████████████████████████████████████████████████████████████| 1.10k/1.10k [00:00<00:00, 1.09MB/s]
cross_visual.py: 100%|████████████████████████████████████████████████████████████| 32.6k/32.6k [00:00<00:00, 32.6MB/s]
model-00008-of-00008.safetensors: 100%|███████████████████████████████████████████| 1.78G/1.78G [01:10<00:00, 25.2MB/s]
I:\Image Captioning\GPT4V-Image-Captioner\myenv\lib\site-packages\huggingface_hub\file_download.py:149: UserWarning: `huggingface_hub` cache-system uses symlinks by default to efficiently store duplicated files but your machine does not support them in I:\Image Captioning\GPT4V-Image-Captioner. Caching files will still work but in a degraded version that might require more space on your disk. This warning can be disabled by setting the `HF_HUB_DISABLE_SYMLINKS_WARNING` environment variable. For more details, see https://huggingface.co/docs/huggingface_hub/how-to-cache#limitations.7, 14.8MB/s]
To support symlinks on Windows, you either need to activate Developer Mode or to run Python as an administrator. In order to see activate developer mode, see this article: https://docs.microsoft.com/en-us/windows/apps/get-started/enable-your-device-for-developmentetensors: 100%|██████████████████████████████████████████▉| 1.78G/1.78G [01:10<00:00, 11.5MB/s]
  warnings.warn(message)
model.safetensors.index.json: 100%|█████████████████████████████████████████████████| 177k/177k [00:00<00:00, 6.77MB/s]
modeling_cogagent.py: 100%|███████████████████████████████████████████████████████████████| 42.5k/42.5k [00:00<?, ?B/s]
util.py: 100%|████████████████████████████████████████████████████████████████████████████| 19.0k/19.0k [00:00<?, ?B/s]
visual.py: 100%|██████████████████████████████████████████████████████████████████████████| 5.45k/5.45k [00:00<?, ?B/s]
model-00003-of-00008.safetensors: 100%|███████████████████████████████████████████| 4.98G/4.98G [03:02<00:00, 27.3MB/s]
model-00007-of-00008.safetensors: 100%|███████████████████████████████████████████| 4.95G/4.95G [03:13<00:00, 25.5MB/s]
model-00004-of-00008.safetensors: 100%|███████████████████████████████████████████| 4.98G/4.98G [03:59<00:00, 20.8MB/s]
model-00001-of-00008.safetensors: 100%|███████████████████████████████████████████| 4.97G/4.97G [04:13<00:00, 19.6MB/s]
model-00006-of-00008.safetensors: 100%|███████████████████████████████████████████| 4.95G/4.95G [04:17<00:00, 19.2MB/s]
model-00002-of-00008.safetensors: 100%|███████████████████████████████████████████| 4.98G/4.98G [05:11<00:00, 16.0MB/s]
model-00005-of-00008.safetensors: 100%|███████████████████████████████████████████| 4.98G/4.98G [05:14<00:00, 15.8MB/s]
Fetching 18 files: 100%|███████████████████████████████████████████████████████████████| 18/18 [05:16<00:00, 17.61s/it]
The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.3.8MB/s]
0it [00:00, ?it/s]08.safetensors:  28%|████████████▏                              | 1.41G/4.98G [04:17<01:56, 30.6MB/s]
bin I:\Image Captioning\GPT4V-Image-Captioner\myenv\lib\site-packages\bitsandbytes\libbitsandbytes_cpu.so:05, 59.8MB/s]
I:\Image Captioning\GPT4V-Image-Captioner\myenv\lib\site-packages\bitsandbytes\cextension.py:34: UserWarning: The installed version of bitsandbytes was compiled without GPU support. 8-bit optimizers, 8-bit multiplication, and GPU quantization are unavailable.
  warn("The installed version of bitsandbytes was compiled without GPU support. "
function 'cadam32bit_grad_fp32' not found
[2024-02-14 03:14:37,126] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-02-14 03:14:37,674] torch.distributed.elastic.multiprocessing.redirects: [WARNING] NOTE: Redirects are currently not supported in Windows or MacOs.
WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for:
    PyTorch 2.1.1+cu121 with CUDA 1201 (you have 2.1.1+cpu)
    Python  3.10.11 (you have 3.10.11)
  Please reinstall xformers (see https://github.com/facebookresearch/xformers#installing-xformers)
  Memory-efficient attention, SwiGLU, sparse and more won't be available.
  Set XFORMERS_MORE_DETAILS=1 for more details

This is the output from installing dependencies through api like seen in the photo:

Not installed libraries: Pillow
Requirement already satisfied: Pillow in i:\image captioning\gpt4v-image-captioner\myenv\lib\site-packages (10.2.0)
Running on local URL:  http://127.0.0.1:8848

To create a public link, set `share=True` in `launch()`.
Use CN
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░▓╫░ torch...
Looking in indexes: https://mirror.baidu.com/pypi/simple
Looking in links: https://mirror.sjtu.edu.cn/pytorch-wheels/torch_stable.html
Collecting torch==2.1.2+cu121
  Downloading https://mirror.sjtu.edu.cn/pytorch-wheels/cu121/torch-2.1.2%2Bcu121-cp310-cp310-win_amd64.whl (2473.9 MB)
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Collecting torchvision==0.16.2+cu121
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Collecting sympy (from torch==2.1.2+cu121)
  Downloading https://mirror.baidu.com/pypi/packages/d2/05/e6600db80270777c4a64238a98d442f0fd07cc8915be2a1c16da7f2b9e74/sympy-1.12-py3-none-any.whl (5.7 MB)
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Requirement already satisfied: urllib3<3,>=1.21.1 in i:\image captioning\gpt4v-image-captioner\myenv\lib\site-packages (from requests->torchvision==0.16.2+cu121) (2.2.0)
Requirement already satisfied: certifi>=2017.4.17 in i:\image captioning\gpt4v-image-captioner\myenv\lib\site-packages (from requests->torchvision==0.16.2+cu121) (2024.2.2)
Collecting mpmath>=0.19 (from sympy->torch==2.1.2+cu121)
  Downloading https://mirror.baidu.com/pypi/packages/43/e3/7d92a15f894aa0c9c4b49b8ee9ac9850d6e63b03c9c32c0367a13ae62209/mpmath-1.3.0-py3-none-any.whl (536 kB)
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Installing collected packages: mpmath, sympy, torch, torchvision
Successfully installed mpmath-1.3.0 sympy-1.12 torch-2.1.2+cu121 torchvision-0.16.2+cu121
░▓╫░ bitsandbytes...
Looking in indexes: https://jihulab.com/api/v4/projects/140618/packages/pypi/simple
Collecting bitsandbytes==0.41.1
  Downloading https://jihulab.com/api/v4/projects/140618/packages/pypi/files/92258b5461c51e54fe9c6ab256aa61f42eee82423ecb8b36ba27a7024b743cc3/bitsandbytes-0.41.1-py3-none-win_amd64.whl (152.7 MB)
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Requirement already satisfied: scipy in i:\image captioning\gpt4v-image-captioner\myenv\lib\site-packages (from bitsandbytes==0.41.1) (1.12.0)
Requirement already satisfied: numpy<1.29.0,>=1.22.4 in i:\image captioning\gpt4v-image-captioner\myenv\lib\site-packages (from scipy->bitsandbytes==0.41.1) (1.26.3)
Installing collected packages: bitsandbytes
Successfully installed bitsandbytes-0.41.1
Looking in indexes: https://mirror.baidu.com/pypi/simple
Processing i:\image captioning\gpt4v-image-captioner\install_script\deepspeed-0.11.2+8ce7471-py3-none-any.whl
Collecting hjson (from deepspeed==0.11.2+8ce7471)
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Collecting ninja (from deepspeed==0.11.2+8ce7471)
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Collecting psutil (from deepspeed==0.11.2+8ce7471)
  Downloading https://mirror.baidu.com/pypi/packages/93/52/3e39d26feae7df0aa0fd510b14012c3678b36ed068f7d78b8d8784d61f0e/psutil-5.9.8-cp37-abi3-win_amd64.whl (255 kB)
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Collecting py-cpuinfo (from deepspeed==0.11.2+8ce7471)
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Collecting pynvml (from deepspeed==0.11.2+8ce7471)
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Requirement already satisfied: mpmath>=0.19 in i:\image captioning\gpt4v-image-captioner\myenv\lib\site-packages (from sympy->torch->deepspeed==0.11.2+8ce7471) (1.3.0)
Installing collected packages: py-cpuinfo, ninja, hjson, pynvml, psutil, deepspeed
Successfully installed deepspeed-0.11.2+8ce7471 hjson-3.0.2 ninja-1.11.1.1 psutil-5.9.8 py-cpuinfo-9.0.0 pynvml-11.5.0
Looking in indexes: https://mirror.baidu.com/pypi/simple
Collecting SwissArmyTransformer>=0.4.9 (from -r ./install_script/require.txt (line 1))
  Downloading https://mirror.baidu.com/pypi/packages/3f/ef/08053493fb128d5928a15c496fe775d73f12dc1fcfe5e8cbfa65e5cb5da4/SwissArmyTransformer-0.4.11-py3-none-any.whl (2.4 MB)
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Collecting transformers>=4.36.1 (from -r ./install_script/require.txt (line 2))
  Downloading https://mirror.baidu.com/pypi/packages/85/f6/c5065913119c41ecad148c34e3a861f719e16b89a522287213698da911fc/transformers-4.37.2-py3-none-any.whl (8.4 MB)
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Collecting spacy>=3.6.0 (from -r ./install_script/require.txt (line 3))
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Collecting seaborn>=0.13.0 (from -r ./install_script/require.txt (line 4))
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Collecting loguru~=0.7.2 (from -r ./install_script/require.txt (line 5))
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Collecting streamlit>=1.29.0 (from -r ./install_script/require.txt (line 6))
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Collecting timm>=0.9.12 (from -r ./install_script/require.txt (line 7))
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Collecting accelerate>=0.25.0 (from -r ./install_script/require.txt (line 8))
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Collecting xformers==0.0.23 (from -r ./install_script/require.txt (line 10))
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Collecting openai>=1.4.0 (from -r ./install_script/require.txt (line 13))
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Collecting uvicorn~=0.24.0 (from -r ./install_script/require.txt (line 16))
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Collecting torch==2.1.1 (from xformers==0.0.23->-r ./install_script/require.txt (line 10))
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Installing collected packages: sentencepiece, cymem, cpm-kernels, braceexpand, zipp, xxhash, win32-setctime, webdataset, watchdog, wasabi, validators, urllib3, tzlocal, tornado, toml, tenacity, spacy-loggers, spacy-legacy, smmap, smart-open, safetensors, regex, pyarrow-hotfix, pyarrow, protobuf, murmurhash, langcodes, jmespath, fsspec, einops, distro, dill, cloudpathlib, catalogue, cachetools, blis, blinker, uvicorn, torch, tensorboardX, srsly, pydeck, preshed, multiprocess, loguru, importlib-metadata, gitdb, botocore, xformers, torchvision, seaborn, s3transfer, openai, gitpython, confection, weasel, tokenizers, timm, thinc, datasets, boto3, accelerate, transformers, streamlit, spacy, SwissArmyTransformer
  Attempting uninstall: urllib3
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  Attempting uninstall: torch
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  Attempting uninstall: torchvision
    Found existing installation: torchvision 0.16.2+cu121
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Successfully installed SwissArmyTransformer-0.4.11 accelerate-0.26.1 blinker-1.7.0 blis-0.7.11 boto3-1.34.34 botocore-1.34.34 braceexpand-0.1.7 cachetools-5.3.2 catalogue-2.0.10 cloudpathlib-0.16.0 confection-0.1.4 cpm-kernels-1.0.11 cymem-2.0.8 datasets-2.16.1 dill-0.3.7 distro-1.9.0 einops-0.7.0 fsspec-2023.10.0 gitdb-4.0.11 gitpython-3.1.41 importlib-metadata-7.0.1 jmespath-1.0.1 langcodes-3.3.0 loguru-0.7.2 multiprocess-0.70.15 murmurhash-1.0.10 openai-1.11.1 preshed-3.0.9 protobuf-4.25.2 pyarrow-15.0.0 pyarrow-hotfix-0.6 pydeck-0.8.1b0 regex-2023.12.25 s3transfer-0.10.0 safetensors-0.4.2 seaborn-0.13.2 sentencepiece-0.1.99 smart-open-6.4.0 smmap-5.0.1 spacy-3.7.2 spacy-legacy-3.0.12 spacy-loggers-1.0.5 srsly-2.4.8 streamlit-1.31.0 tenacity-8.2.3 tensorboardX-2.6.2.2 thinc-8.2.2 timm-0.9.12 tokenizers-0.15.1 toml-0.10.2 torch-2.1.1 torchvision-0.16.1 tornado-6.4 transformers-4.37.2 tzlocal-5.2 urllib3-2.0.7 uvicorn-0.24.0.post1 validators-0.22.0 wasabi-1.1.2 watchdog-3.0.0 weasel-0.3.4 webdataset-0.2.86 win32-setctime-1.1.0 xformers-0.0.23 xxhash-3.4.1 zipp-3.17.0

Install_windows.bat output:

Python installed.
╒²╘┌┤┤╜¿╨Θ─Γ╗╖╛│...
Use CN
Installing deps...
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Looking in indexes: https://mirror.baidu.com/pypi/simple
Requirement already satisfied: pip in i:\image captioning\gpt4v-image-captioner\myenv\lib\site-packages (23.0.1)
Collecting pip
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Installing collected packages: pip
  Attempting uninstall: pip
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    Uninstalling pip-23.0.1:
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Successfully installed pip-24.0
Looking in indexes: https://mirror.baidu.com/pypi/simple
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Collecting requests (from -r ./install_script/requirements.txt (line 8))
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  Installing build dependencies ... done
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Building wheels for collected packages: GPUtil, ffmpy
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Successfully installed GPUtil-1.4.0 Pillow-10.2.0 aiofiles-23.2.1 aiohttp-3.9.3 aiosignal-1.3.1 altair-5.2.0 annotated-types-0.6.0 anyio-4.2.0 async-timeout-4.0.3 attrs-23.2.0 certifi-2024.2.2 charset-normalizer-3.3.2 click-8.1.7 colorama-0.4.6 contourpy-1.2.0 cycler-0.12.1 dashscope-1.14.1 exceptiongroup-1.2.0 fastapi-0.109.2 ffmpy-0.3.1 filelock-3.13.1 fonttools-4.47.2 frozenlist-1.4.1 fsspec-2024.2.0 gradio-4.16.0 gradio-client-0.8.1 h11-0.14.0 httpcore-1.0.2 httpx-0.26.0 huggingface_hub-0.20.3 idna-3.6 importlib-resources-6.1.1 jinja2-3.1.3 jsonschema-4.21.1 jsonschema-specifications-2023.12.1 kiwisolver-1.4.5 markdown-it-py-3.0.0 markupsafe-2.1.5 matplotlib-3.8.2 mdurl-0.1.1 multidict-6.0.5 networkx-3.2.1 numpy-1.26.3 orjson-3.9.13 packaging-23.2 pandas-2.2.0 pydantic-2.6.0 pydantic-core-2.16.1 pydub-0.25.1 pygments-2.17.2 pyparsing-3.1.1 python-dateutil-2.8.2 python-multipart-0.0.7 pytz-2024.1 pyyaml-6.0.1 referencing-0.33.0 requests-2.31.0 rich-13.7.0 rpds-py-0.17.1 ruff-0.2.0 scipy-1.12.0 semantic-version-2.10.0 shellingham-1.5.4 six-1.16.0 sniffio-1.3.0 starlette-0.36.3 tomlkit-0.12.0 toolz-0.12.1 tqdm-4.66.1 typer-0.9.0 typing-extensions-4.9.0 tzdata-2023.4 urllib3-2.2.0 uvicorn-0.27.0.post1 websockets-11.0.3 wordcloud-1.9.3 yarl-1.9.4
Install completed, please run Start to open the GUI
░▓╫░═Ω▒╧ú¼╟δ╘╦╨╨Start┤≥┐¬GUI
Press any key to continue . . .

切换ConVLM模型时报错： ========Use torch type as:torch.bfloat16 with device:cuda======== Traceback (most recent call last): File "/biao/openai_api.py", line 462, in <module> load_mod(MODEL_PATH, STATE_MOD) File "/biao/openai_api.py", line 367, in load_mod tokenizer = LlamaTokenizer.from_pretrained( File "/biao/myenv/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1450, in __getattribute__ requires_backends(cls, cls._backends) File "/biao/myenv/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1438, in requires_backends raise ImportError("".join(failed)) ImportError: LlamaTokenizer requires the SentencePiece library but it was not found in your environment. Checkout the instructions on the installation page of its repo: https://github.com/google/sentencepiece#installation and follow the ones that match your environment. Please note that you may need to restart your runtime after installation.

环境报错，一开始报错提示没有torch，然后我手动装了一遍环境。好不容易装好了结果又有新的报错（如图所示），怎么也解决不了。ChatGPT说要安装一个SentencePiece库，试了各种方法安装，chatgpt问爆了也没解决问题，整了差不多12个小时，心态爆炸。作者能帮忙看看吗？

installCog Bug

pip install torch==2.1.2+cu121 torchvision==0.16.2+cu121 --extra-index-url https://download.pytorch.org/whl/cu118
should be pip install torch==2.1.2+cu121 torchvision==0.16.2+cu121 --extra-index-url https://download.pytorch.org/whl/cu121

API does not change on switch

It just says http://127.0.0.1:8000/v1/chat/completions, which does not work. http://127.0.0.1:8000/docs also do not mention any useful methods. I have tried with moondream and vqa, downloaded and installed

Bug: Trying to look for powershell in linux?

I'm running under Linux:
When i switch API i get the following in the terminal:

-ExecutionPolicy: 1: powershell.exe: not found
Retrying...
Retrying...
Retrying...

Response generated, but i can't generated the txt file with COG

I'm not sure why it happens, when i use normal gpt4v it works, but when i use COG i get

Failed to parse the API response: 'output'
{"model":"gpt-4-vision-preview","object":"chat.completion","choices":[{"index":0,"message":{"role":"assistant","content":"The image features a cat with neon-colored eyes, set against a space-themed background with geometric shapes and a moon. The cat is wearing a shirt with a circular symbol. The image quality is high, and it's a close-up shot of the cat's face. The camera used was a Canon EOS R5 with a 50mm lens, and the image was taken in RAW format.","name":null}}],"created":1706983380,"usage":{"prompt_tokens":526,"total_tokens":0,"completion_tokens":-526}}

Can you tell me why is slow working after finishing 200 captioning?

请问max_tokens在哪里修改呢

输出时会遇到输出不全的问题，想要修改max_tokens

使用COG无法安装apex库

请问这个怎么解决啊？apex好像不支持windows

建议加入 openbmb/OmniLMM-12B，实测打标效果比 cogagent-vqa 好

openbmb/OmniLMM-12B的在线体验地址 http://120.92.209.146:8081/

本地部署需要23.8G VRAM，在2080Ti 22G上开共享显存可以运行

HTTP Error: 404 Client Error: Not Found for url: https://api.openai.com/v1/chat/completions

i got an api from openai, i got this when using gpt-4-vision-preview , does anybody know what is wrong?

HTTP Error: 500 Server Error: Internal Server Error for url: http://127.0.0.1:8000/v1/chat/completions

用vqa报错

Error: "install_cn.ps1 cannot be loaded because running scripts is disabled on this system"

I redownloaded and now have this issue when trying to install via the install_windows.bat file. I didn't have this issue previously.

Python installed.
Use CN
File I:\GPT4V-Image-Captioner\install_script\![Screenshot 2024-01-19 012838](https://github.com/jiayev/GPT4V-Image-Captioner/assets/22781570/3eaab6f8-114a-4349-8361-aded2a85d7d3). For more information, see about_Execution_Policies at https:/go.microsoft.com/fwlink/?LinkID=135170.
    + CategoryInfo          : SecurityError: (:) [], ParentContainsErrorRecordException
    + FullyQualifiedErrorId : UnauthorizedAccess
Press any key to continue . . .

希望做期不同打标模型对比视频

现在提供了好几种模型，包括云端及本地部署的，gpt4v api不容易获得，希望作者大大能做期视频对比说明