---
tags:
- vision
- coin
- clip
- coin-retrieval
- coin-recognition
- coin-search-engine
- multi-modal learning
widget:
- src: >-
    https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-dog-music.png
  candidate_labels: playing music, playing sports
  example_title: Cat & Dog
license: apache-2.0
library_name: transformers
pipeline_tag: feature-extraction
---

# Coin-CLIP 🪙 : Enhancing Coin Image Retrieval with CLIP

## Model Details / 模型细节

This model (**Coin-CLIP**) is built upon 
OpenAI's **[CLIP](https://huggingface.co/openai/clip-vit-base-patch32) (ViT-B/32)** model and fine-tuned on 
a dataset of more than `340,000` coin images using contrastive learning techniques. This specialized model is designed to significantly improve feature extraction for coin images, leading to more accurate image-based search capabilities. Coin-CLIP combines the power of Visual Transformer (ViT) with CLIP's multimodal learning capabilities, specifically tailored for the numismatic domain.

**Key Features:**
- State-of-the-art coin image retrieval;
- Enhanced feature extraction for numismatic images;
- Seamless integration with CLIP's multimodal learning.

本模型（**Coin-CLIP**）
在 OpenAI 的 **[CLIP](https://huggingface.co/openai/clip-vit-base-patch32) (ViT-B/32)** 模型基础上，利用对比学习技术在超过 `340,000` 张硬币图片数据上微调得到的。
**Coin-CLIP** 旨在提高模型针对硬币图片的特征提取能力，从而实现更准确的以图搜图功能。该模型结合了视觉变换器（ViT）的强大功能和 CLIP 的多模态学习能力，并专门针对硬币图片进行了优化。



## Comparison: Coin-CLIP vs. CLIP / 效果对比

#### Example 1 (Left: Coin-CLIP; Right: CLIP)

![1. Coin-CLIP vs. CLIP](https://www.notion.so/image/https%3A%2F%2Fprod-files-secure.s3.us-west-2.amazonaws.com%2F9341931a-53f0-48e1-b026-0f1ad17b457c%2F4b047305-0bf2-4809-acc6-94fd412d5307%2FUntitled.gif?table=block&id=78225b2b-49b4-4a18-b33c-c4530a6e8330)

#### Example 2 (Left: Coin-CLIP; Right: CLIP)

![2. Coin-CLIP vs. CLIP](https://www.notion.so/image/https%3A%2F%2Fprod-files-secure.s3.us-west-2.amazonaws.com%2F9341931a-53f0-48e1-b026-0f1ad17b457c%2F14376459-bedd-4d82-a178-fde391fd70d0%2FUntitled.gif?table=block&id=99ed5179-bcab-4c58-b6d8-1a77bffe79f7)

More examples can be found: [breezedeus/Coin-CLIP: Coin CLIP](https://github.com/breezedeus/Coin-CLIP) .



## Usage and Limitations / 使用和限制

- **Usage**: This model is primarily used for extracting representation vectors from coin images, enabling efficient and precise image-based searches in a coin image database.
- **Limitations**: As the model is trained specifically on coin images, it may not perform well on non-coin images.




- **用途**：此模型主要用于提取硬币图片的表示向量，以实现在硬币图像库中进行高效、精确的以图搜图。
- **限制**：由于模型是针对硬币图像进行训练的，因此在处理非硬币图像时可能效果不佳。



## Documents / 文档

- Base Model: [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32)

  

## Model Use / 模型使用

### Transformers

```python
from PIL import Image
import requests

import torch.nn.functional as F
from transformers import CLIPProcessor, CLIPModel

model = CLIPModel.from_pretrained("breezedeus/coin-clip-vit-base-patch32")
processor = CLIPProcessor.from_pretrained("breezedeus/coin-clip-vit-base-patch32")

image_fp = "path/to/coin_image.jpg"
image = Image.open(image_fp).convert("RGB")

inputs = processor(images=image, return_tensors="pt")
img_features = model.get_image_features(**inputs)
img_features = F.normalize(img_features, dim=1)
```

### Tool / 工具

To further simplify the use of the **Coin-CLIP** model, we provide a simple Python library [breezedeus/Coin-CLIP: Coin CLIP](https://github.com/breezedeus/Coin-CLIP) for quickly building a coin image retrieval engine.

为了进一步简化 **Coin-CLIP** 模型的使用，我们提供了一个简单的 Python 库 [breezedeus/Coin-CLIP: Coin CLIP](https://github.com/breezedeus/Coin-CLIP)，以便快速构建硬币图像检索引擎。

#### Install

```bash
pip install coin_clip
```


#### Extract Feature Vectors

```python
from coin_clip import CoinClip

# Automatically download the model from Huggingface
model = CoinClip(model_name='breezedeus/coin-clip-vit-base-patch32')
images = ['examples/10_back.jpg', 'examples/16_back.jpg']
img_feats, success_ids = model.get_image_features(images)
print(img_feats.shape)  # --> (2, 512)
```

More Tools can be found: [breezedeus/Coin-CLIP: Coin CLIP](https://github.com/breezedeus/Coin-CLIP) .


## Training Data / 训练数据

The model was trained on a specialized coin image dataset. This dataset includes images of various currencies' coins.



本模型使用的是专门的硬币图像数据集进行训练。这个数据集包含了多种货币的硬币图片。

## Training Process / 训练过程

The model was fine-tuned on the OpenAI CLIP (ViT-B/32) pretrained model using a coin image dataset. The training process involved Contrastive Learning fine-tuning techniques and parameter settings.



模型是在 OpenAI 的 CLIP (ViT-B/32) 预训练模型的基础上，使用硬币图像数据集进行微调。训练过程采用了对比学习的微调技巧和参数设置。

## Performance / 性能

This model demonstrates excellent performance in coin image retrieval tasks. 



该模型在硬币图像检索任务上展现了优异的性能。



## Feedback / 反馈

> Where to send questions or comments about the model.

Welcome to contact the author [Breezedeus](https://www.breezedeus.com/join-group).

欢迎联系作者  [Breezedeus](https://www.breezedeus.com/join-group) 。