Update README.md

README.md

@@ -1,214 +1,9 @@
-<p align="center">
-  <img src="assets/logo2.png" height=65>
-</p>
-
-<div align="center">
-
-⏬[**Download Models**](#-download-models) **|** 💻[**How to Test**](#-how-to-test)
-
-</div>
-
-Official implementation of T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models.
-
-#### [Paper](https://arxiv.org/abs/2302.08453)
-
-<p align="center">
-  <img src="assets/overview1.png" height=250>
-</p>
-
-We propose T2I-Adapter, a **simple and small (~70M parameters, ~300M storage space)** network that can provide extra guidance to pre-trained text-to-image models while **freezing** the original large text-to-image models.
-
-T2I-Adapter aligns internal knowledge in T2I models with external control signals.
-We can train various adapters according to different conditions, and achieve rich control and editing effects.
-
-<p align="center">
-  <img src="assets/teaser.png" height=500>
-</p>
-
-### ⏬ Download Models
-
-Put the downloaded models in the `T2I-Adapter/models` folder.
-
-1. The **T2I-Adapters** can be download from <https://huggingface.co/TencentARC/T2I-Adapter>.
-2. The pretrained **Stable Diffusion v1.4** models can be download from <https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/tree/main>. You need to download the `sd-v1-4.ckpt
-` file.
-3. [Optional] If you want to use **Anything v4.0** models, you can download the pretrained models from <https://huggingface.co/andite/anything-v4.0/tree/main>. You need to download the `anything-v4.0-pruned.ckpt` file.
-4. The pretrained **clip-vit-large-patch14** folder can be download from <https://huggingface.co/openai/clip-vit-large-patch14/tree/main>. Remember to download the whole folder!
-5. The pretrained keypose detection models include FasterRCNN (human detection) from <https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth> and HRNet (pose detection) from <https://download.openmmlab.com/mmpose/top_down/hrnet/hrnet_w48_coco_256x192-b9e0b3ab_20200708.pth>.
-
-After downloading, the folder structure should be like this:
-
-<p align="center">
-  <img src="assets/downloaded_models.png" height=100>
-</p>
-
-### 🔧 Dependencies and Installation
-
-- Python >= 3.6 (Recommend to use [Anaconda](https://www.anaconda.com/download/#linux) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html))
-- [PyTorch >= 1.4](https://pytorch.org/)
-```bash
-pip install -r requirements.txt
-```
-- If you want to use the full function of keypose-guided generation, you need to install MMPose. For details please refer to <https://github.com/open-mmlab/mmpose>.
-
-### 💻 How to Test
-
-- The results are in the `experiments` folder.
-- If you want to use the `Anything v4.0`, please add `--ckpt models/anything-v4.0-pruned.ckpt` in the following commands.
-
-#### **For Simple Experience**
-
-> python app.py
-
-#### **Sketch Adapter**
-
-- Sketch to Image Generation
-
-> python test_sketch.py --plms --auto_resume --prompt "A car with flying wings" --path_cond examples/sketch/car.png --ckpt models/sd-v1-4.ckpt --type_in sketch
-
-- Image to Image Generation
-
-> python test_sketch.py --plms --auto_resume --prompt "A beautiful girl" --path_cond examples/anything_sketch/human.png --ckpt models/sd-v1-4.ckpt --type_in image
-
-- Generation with **Anything** setting
-
-> python test_sketch.py --plms --auto_resume --prompt "A beautiful girl" --path_cond examples/anything_sketch/human.png --ckpt models/anything-v4.0-pruned.ckpt --type_in image
-
-##### Gradio Demo
-<p align="center">
-  <img src="assets/gradio_sketch.png">
-</p>
-You can use gradio to experience all these three functions at once. CPU is also supported by setting device to 'cpu'.
-
-```bash
-python gradio_sketch.py
-```
-
-#### **Keypose Adapter**
-
-- Keypose to Image Generation
-
-> python test_keypose.py --plms --auto_resume --prompt "A beautiful girl" --path_cond examples/keypose/iron.png --type_in pose
-
-- Image to Image Generation
-
-> python test_keypose.py --plms --auto_resume --prompt "A beautiful girl" --path_cond examples/sketch/human.png --type_in image
-
-- Generation with **Anything** setting
-
-> python test_keypose.py --plms --auto_resume --prompt "A beautiful girl" --path_cond examples/sketch/human.png --ckpt models/anything-v4.0-pruned.ckpt --type_in image
-
-##### Gradio Demo
-<p align="center">
-  <img src="assets/gradio_keypose.png">
-</p>
-You can use gradio to experience all these three functions at once. CPU is also supported by setting device to 'cpu'.
-
-```bash
-python gradio_keypose.py
-```
-
-#### **Segmentation Adapter**
-
-> python test_seg.py --plms --auto_resume --prompt "A black Honda motorcycle parked in front of a garage" --path_cond examples/seg/motor.png
-
-#### **Two adapters: Segmentation and Sketch Adapters**
-
-> python test_seg_sketch.py --plms --auto_resume --prompt "An all white kitchen with an electric stovetop" --path_cond examples/seg_sketch/mask.png --path_cond2 examples/seg_sketch/edge.png
-
-#### **Local editing with adapters**
-
-> python test_sketch_edit.py --plms --auto_resume --prompt "A white cat" --path_cond examples/edit_cat/edge_2.png --path_x0 examples/edit_cat/im.png --path_mask examples/edit_cat/mask.png
-
-## Stable Diffusion + T2I-Adapters (only ~70M parameters, ~300M storage space)
-
-The following is the detailed structure of a **Stable Diffusion** model with the **T2I-Adapter**.
-<p align="center">
-  <img src="assets/overview2.png" height=300>
-</p>
-
-<!-- ## Web Demo
-
-* All the usage of three T2I-Adapters (i.e, sketch, keypose and segmentation) are integrated into [Huggingface Spaces]() 🤗 using [Gradio](). Have fun with the Web Demo.  -->
-
-## 🚀 Interesting Applications
-
-### Stable Diffusion results guided with the sketch T2I-Adapter
-
-The corresponding edge maps are predicted by PiDiNet. The sketch T2I-Adapter can well generalize to other similar sketch types, for example, sketches from the Internet and user scribbles.
-
-<p align="center">
-  <img src="assets/sketch_base.png" height=800>
-</p>
-
-### Stable Diffusion results guided with the keypose T2I-Adapter
-
-The keypose results predicted by the [MMPose](https://github.com/open-mmlab/mmpose).
-With the keypose guidance, the keypose T2I-Adapter can also help to generate animals with the same keypose, for example, pandas and tigers.
-
-<p align="center">
-  <img src="assets/keypose_base.png" height=600>
-</p>
-
-### T2I-Adapter with Anything-v4.0
-
-Once the T2I-Adapter is trained, it can act as a **plug-and-play module** and can be seamlessly integrated into the finetuned diffusion models **without re-training**, for example, Anything-4.0.
-
-#### ✨ Anything results with the plug-and-play sketch T2I-Adapter (no extra training)
-
-<p align="center">
-  <img src="assets/sketch_anything.png" height=600>
-</p>
-
-#### Anything results with the plug-and-play keypose T2I-Adapter (no extra training)
-
-<p align="center">
-  <img src="assets/keypose_anything.png" height=600>
-</p>
-
-### Local editing with the sketch adapter
-
-When combined with the inpaiting mode of Stable Diffusion, we can realize local editing with user specific guidance.
-
-#### ✨ Change the head direction of the cat
-
-<p align="center">
-  <img src="assets/local_editing_cat.png" height=300>
-</p>
-
-#### ✨ Add rabbit ears on the head of the Iron Man.
-
-<p align="center">
-  <img src="assets/local_editing_ironman.png" height=400>
-</p>
-
-### Combine different concepts with adapter
-
-Adapter can be used to enhance the SD ability to combine different concepts.
-
-####  ✨ A car with flying wings. / A doll in the shape of letter ‘A’.
-
-<p align="center">
-  <img src="assets/enhance_SD2.png" height=600>
-</p>
-
-### Sequential editing with the sketch adapter
-
-We can realize the sequential editing with the adapter guidance.
-
-<p align="center">
-  <img src="assets/sequential_edit.png">
-</p>
-
-### Composable Guidance with multiple adapters
-
-Stable Diffusion results guided with the segmentation and sketch adapters together.
-
-<p align="center">
-  <img src="assets/multiple_adapters.png">
-</p>
-
-
-![visitors](https://visitor-badge.glitch.me/badge?page_id=TencentARC/T2I-Adapter)
-
-Logo materials: [adapter](https://www.flaticon.com/free-icon/adapter_4777242), [lightbulb](https://www.flaticon.com/free-icon/lightbulb_3176369)
+---
+license: openrail
+title: T2I-Adapter
+sdk: gradio
+emoji: 😻
+colorFrom: pink
+colorTo: blue
+pinned: false
+---