How do I make a dataset for vision models?

🤗Datasets
1

So I was reading this blog Vision Language Models Explained on fine-tuning LLaVA from a dataset from HF, and I was wondering - How can I upload my custom dataset on HF to do that same with my data? Can anyone help me out with that?

Currently, I have an images folder that contains all the images and have a file named data.json in my root folder. How will I process would look like? I already read some tutorials on docs.

data.json:

[
  {
    "role": "user",
    "content": [
      { "type": "text", "text": "What’s in this image?" },
      { "type": "image" }
    ]
  },
  { "role": "assistant", "content": [{ "type": "text", "text": "DOG" }] },
  {
    "role": "user",
    "content": [
      { "type": "text", "text": "What’s in this image?" },
      { "type": "image" }
    ]
  },
  { "role": "assistant", "content": [{ "type": "text", "text": "CAT" }] },
  {
    "role": "user",
    "content": [
      { "type": "text", "text": "What’s in this image?" },
      { "type": "image" }
    ]
  },
  { "role": "assistant", "content": [{ "type": "text", "text": "DUCK" }] }
]
1 Like
2

Any idea? @lhoestq @mariosasko

3

In the blog they use the dataset at HuggingFaceH4/llava-instruct-mix-vsft ¡ Datasets at Hugging Face, so you should use the same format. I notice your already have the JSON part in the right format, you just need to associate the JSON part with the images.

You can do so programmatically:

from datasets import Dataset, Image, Sequence

ds = Dataset.from_dict({"messages": your_data_json_messages_list})
ds = ds.add_column("images", [[img_path] for img_path in img_paths])  # contains lists of 1 image
ds = ds.cast_column("images", Sequence(Image()))  # from string type to image type

# Optionally push to the HF Hub
ds.push_to_hub("username/datasetname")
4

Getting this error “ValueError: Failed to concatenate on axis=1 because tables don’t have the same number of rows”

import os
import json
from datasets import Dataset, Image, Sequence

with open("data.json", "r") as f:
    your_data_json = json.load(f)

img_folder = "images/"
img_paths = [os.path.join(img_folder, img_name) for img_name in os.listdir(img_folder) if img_name.endswith(('.jpg', '.jpeg', '.png'))]

ds = Dataset.from_dict({"messages": your_data_json})

ds = ds.add_column("images", [[img_path] for img_path in img_paths])  

ds = ds.cast_column("images", Sequence(Image()))

ds.push_to_hub("marksuccsmfewercoc/test")
5

You should have as many images as items in your messages list for it to work. In particular you can make sure each item in the messages list is a list of one user message and one assistant message.

6

But the LLava dataset and mine dataset look very different how to fix it?

here is what the correct dataset looks like HuggingFaceH4/llava-instruct-mix-vsft ¡ Datasets at Hugging Face and here is what my dataset looks like marksuccsmfewercoc/test ¡ Datasets at Hugging Face

7

The messages column should contain lists (one list per image), for example the first list can look like

[
  {
    "content": [ { "index": null, "text": "What’s in this image?\n", "type": "text" }, { "index": 0, "text": null, "type": "image" } ],
    "role": "user"
  },
  {
    "content": [ { "index": null, "text": "DOG", "type": "text" } ],
    "role": "assistant" 
  }
]
8

So what does my JSON file look like? before uploading it to the hub

10

Can you please tell me what’s the correct format to make it work with fine-tuning LLaVA according to the blog by HF?

I just have three images in my images folder.

11

Hey @lhoestq I’m still getting “raise ValueError(“Failed to concatenate on axis=1 because tables don’t have the same number of rows”) ValueError: Failed to concatenate on axis=1 because tables don’t have the same number of rows”.

But when I print the length of images and JSON it prints 3 and 3 which is correct. Any idea about what can be the issue?


import os
import json
from datasets import Dataset, Image, Sequence

with open("data.json", "r") as f:
    your_data_json = json.load(f)

print(len(your_data_json))
print(len(os.listdir('images/')))

ds = Dataset.from_dict({"messages": your_data_json})
ds = ds.add_column("images", [[img_path] for img_path in 'images/']) 
ds = ds.cast_column("images", Sequence(Image()))  

ds.push_to_hub("marksuccsmfewercoc/test")

I don’t understand if both len(your_data_json) value and (len(os.listdir(‘images/’)) are 3 then what’s the issue?

12

Hi ! I think there is a small bug in your code:

- ds = ds.add_column("images", [[img_path] for img_path in 'images/']) 
+ ds = ds.add_column("images", [[img_path] for img_path in os.listdir('images/')])
13

Very confusing, Now I’m getting FileNotFoundError: [Errno 2] No such file or directory: ‘dog.png’ error, But I do have a dog.png file in my images folder

14

Hey @lhoestq I fixed that problem but the images and dataset are not in proper sequence, how to fix this? How to link images with each conversations in the JSON data?