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---
license: apache-2.0
language:
- en
library_name: open_clip
pipeline_tag: zero-shot-image-classification
---
# GenshinCLIP
A simple open-sourced SigLIP model fine-tuned on Genshin Impact's image-text pairs.
The model is far from being perfect, but could still offer some better text-image matching performance in some Genshin Impact scenarios.
## Case Study
| Case | Image | Multiple Choices | CLIPScore<br/>(After Finetune) | CLIPScore<br/>(Before Finetune) |
|------|----------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------|---------------------------------------------------------------------|
| 1 | <img src="https://static.wikia.nocookie.net/gensin-impact/images/2/24/Ganyu_Card.png/revision/latest?cb=20230519012433" height="64"> | 1) This is an image of Kuki Shinobu<br/>2) This is an image of Ganyu<br/>3) This is an image of Keqing<br/>4) This is an image of Liyue | 1) 0.000<br>2) **0.438**<br>3) 0.000<br>4) 0.000 | 1) **1.207e-06**<br/>2) 4.144e-08<br/>3) 1.201e-07<br/>4) 2.212e-08 |
| 2 | <img src="https://static.wikia.nocookie.net/gensin-impact/images/3/33/Qingce_Village.png/revision/latest?cb=20220626161951" height="64"> | 1) This is an area of Liyue<br/>2) This is an area of Mondstadt<br/>3) This is an area of Sumeru<br/>4) This is Qingce Village | 1) 0.016<br>2) 0.000<br>3) 0.001<br>4) **0.233** | 1) 0.015<br/>2) 0.003<br/>3) 0.009<br/>4) **0.377** |
| 3 | <img src="https://static.wikia.nocookie.net/gensin-impact/images/0/0c/Enemy_Boreas.png/revision/latest?cb=20210426192800" height="64"> | 1) This is Andrius Wolf of the North<br/>2) This is Stormterror Dvalin<br/>3) This is Guardian of Apep's Oasis | 1) 1.000<br>2) 0.000<br>3) 0.000 | 1) **0.001**<br/>2) 0.000<br/>3) 0.000 |
| 4 | <img src="https://static.wikia.nocookie.net/gensin-impact/images/2/24/Item_Amakumo_Fruit_Wild.png/revision/latest?cb=20220601235905" height="64"> | 1) This is Amakumo Fruit<br/>2) This is Padisarahs<br/>3) This is Naku Weeds | 1) 0.000<br>2) 0.000<br>3) **0.024** | 1) 9.425e-07<br/>2) 1.207e-06<br/>3) **1.669e-05** |
Note: Case 4 is a bad case. (Correct answer is Amakumo Fruit)
## Intended uses & limitations
You can use the raw model for tasks like zero-shot image classification and image-text retrieval.
### How to use (With OpenCLIP)
Here is how to use this model to perform zero-shot image classification:
```python
import torch
import torch.nn.functional as F
from PIL import Image
import requests
from open_clip import create_model_from_pretrained, get_tokenizer
def preprocess_text(string):
return "Genshin Impact\n" + string
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
# load checkpoint from local path
# model_path = "path/to/open_clip_pytorch_model.bin"
# model_name = "ViT-SO400M-14-SigLIP-384"
# model, preprocess = create_model_from_pretrained(model_name=model_name, pretrained=model_path, device=device)
# tokenizer = get_tokenizer(model_name)
# or load from hub
model, preprocess = create_model_from_pretrained('hf-hub:mrzjy/GenshinImpact-ViT-SO400M-14-SigLIP-384')
tokenizer = get_tokenizer('hf-hub:mrzjy/GenshinImpact-ViT-SO400M-14-SigLIP-384')
# image
image_url = "https://static.wikia.nocookie.net/gensin-impact/images/3/33/Qingce_Village.png"
image = Image.open(requests.get(image_url, stream=True).raw)
image = preprocess(image).unsqueeze(0).to(device)
# text choices
labels = [
"This is an area of Liyue",
"This is an area of Mondstadt",
"This is an area of Sumeru",
"This is Qingce Village"
]
labels = [preprocess_text(l) for l in labels]
text = tokenizer(labels, context_length=model.context_length).to(device)
with torch.autocast(device_type=device.type):
with torch.no_grad():
image_features = model.encode_image(image)
text_features = model.encode_text(text)
image_features = F.normalize(image_features, dim=-1)
image_features = F.normalize(image_features, dim=-1)
text_features = F.normalize(text_features, dim=-1)
text_probs = torch.sigmoid(image_features @ text_features.T * model.logit_scale.exp() + model.logit_bias)
scores = [f"{s:.3f}" for i, s in enumerate(text_probs.tolist()[0])]
print(scores) # [0.016, 0.000, 0.001, 0.233]
```
## Model Card
### SigLIP for GenshinImpact
[SigLIP model](https://huggingface.co/timm/ViT-SO400M-14-SigLIP-384) further fine-tuned on 17k Genshin Impact English text-image pairs at resolution 384x384.
### Training data description
There're currently 17,428 (train) and 918 (validation) text-image pairs used for model training.
All the images and texts are crawled from [Genshin Fandom Wiki](https://genshin-impact.fandom.com/wiki) and are manually parsed to form text-image pairs.
**Image Processing:**
- Size: Resize all images to 384x384 pixels to match the original model training settings.
- Format: Accept images in PNG or GIF format. For GIFs, extract a random frame to create a static image for text-image pairs.
**Text Processing:**
- Source: Text can be from the simple caption attribute of an HTML `<img>` tag or specified web content.
- Format: Prepend all texts with "Genshin Impact" along with some simple template to form natural language sentences.
For example, here are some training image-text pairs:
| Image | Text |
|----------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <img src="img/9361c6fe-dabe-43b3-ae76-9731e4b73e1b.png" height="64"> | Genshin Impact<br/>This is Tainted Water-Splitting Phantasm.<br/>Tainted Hydro Phantasm Idle Waving 2 |
| <img src="img/911d0f58-dc35-4dfb-9afc-79a2d582881b.png" height="64"> | Genshin Impact<br/>This is Annihilation Specialist Mek.<br/>Although the Fontaine Research Institute of Kinetic Energy Engineering... ..., state apparatus enforcing the monopoly on violence. |
| <img src="img/bd94b015-153f-41de-b8d4-049ba29481e3.png" height="64"> | Genshin Impact<br/>Collei<br/>Expressions<br/>a Smiley expression |
| <img src="img/36a956e1-e6af-43bc-a71b-a893fe1bcf9e.png" height="64"> | Genshin Impact<br/>This is the map of viewpoint Nine Pillars of Peace in Cuijue Slope, Minlin, Liyue<br/>Nine shackles of stone were said to have been laid down deep in the valleys of Cuijue Slope to drive off evil and cleanse the world. |
**Data Distribution:**
**Validation Loss Curve**
|