* [maixcam2] optimize projects

Author: lxowalle

docs/doc/assets/ldm_sdv1.5_img2img.jpg

@@ -0,0 +1,122 @@
+---
+title: Running the LCM-LoRA-SDv1-5 Model on MaixPy MaixCAM
+update:
+  - date: 2025-12-03
+    author: lxowalle
+    version: 1.0.0
+    content: Added LCM-LoRA-SDv1-5 code and documentation
+---
+
+## Supported Devices
+
+| Device      | Supported |
+| -------- | ------- |
+| MaixCAM2 | ✅ |
+| MaixCAM  | ❌ |
+
+
+## Introduction to the LCM-LoRA-SDv1-5 Model
+
+LCM-LoRA-SDv1-5 is a model that supports text-to-image and image-to-image generation, based on the StableDiffusion 1.5 LCM project. With this model, you can generate conceptual images for artistic creation—simply provide a text description, and the model will generate an image based on it.
+
+## Running the LCM-LoRA-SDv1-5 Model on MaixPy MaixCAM
+
+### Model and Download Link
+
+If the `LCM-LoRA-SDv1-5` model is not present in the system directory `/root/models` by default, you need to download it manually.
+
+ * Memory requirement: CMM memory 1 GiB. For details, refer to the [Memory Usage Documentation](../pro/memory.md)
+
+ * Download link: https://huggingface.co/sipeed/lcm-lora-sdv1-5-maixcam2
+
+For the download method, refer to the instructions in the [Qwen documentation](../pro/memory.md)
+
+### Running the Model with MaixPy
+
+> Note: MaixPy version `4.12.3` or above is required for support.
+
+This example demonstrates how to use MaixPy to run the LCM-LoRA-SDv1-5 model for both text-to-image and image-to-image generation.
+
+```python
+from maix import sdv1_5
+
+model = sdv1_5.SDV1_5("/root/models/lcm-lora-sdv1-5-maixcam2/ax620e_models")
+model.init(img2img=True)
+model.refer(prompt="A white dog.", save_path="/root/text2img.jpg")
+model.refer(prompt="Replace the dog with a cat.", init_image_path="/root/text2img.jpg", seed=1, save_path="/root/img2img.jpg")
+
+model.deinit()
+```
+Output:
+![](../../assets/ldm_sdv1.5_img2img.jpg)
+
+Explanation:
+1. When performing text-to-image generation, you need to define a `prompt` describing the image you want. The prompt must be written in English, and the generated image will be saved to the path specified by `save_path`.
+2. When performing image-to-image generation, you need to define a prompt describing the content you want to generate`init_image_path` specifies the initial image,`seed` controls randomness in image generation
+The output image will be saved to the path specified by save_path.
+3. Since `sdv1_5` depends on several large Python packages, importing it may take some time. If you want the application to enter the UI quickly during development, you can use `importlib` and `threading` to load the module in the background. Example:
+```python
+from maix import time
+import importlib, threading
+
+class ModuleLoader():
+    def __load_module(self):
+        self.module = importlib.import_module(self.module_name)
+        self.load_ok = True
+        pass
+    def __init__(self, module_name: str):
+        self.module_name = module_name
+        self.module = None
+        self.load_ok = False
+        self.t = threading.Thread(target=self.__load_module)
+        self.t.start()
+    def try_get_module(self, block = True):
+        if self.load_ok:
+            return self.module
+        if block:
+            while not self.load_ok:
+                time.sleep_ms(100)
+            return self.module
+        else:
+            return None
+
+sdv1_5_loader = ModuleLoader("maix.sdv1_5")
+while True:
+    sdv1_5 = sdv1_5_loader.try_get_module(block=False)
+    if sdv1_5 is not None:
+        break
+    time.sleep_ms(1000)
+print(sdv1_5)
+```
+
+### Running the Model with Command Line
+
+Refer to `launcher.py` in the model directory to run the model.
+
+#### Text-to-Image
+```shell
+cd lcm-lora-sdv1-5-maixcam2
+python3 launcher.py --isize 256 --model_dir ax620e_models/ -o "ax620e_txt2img_axe.png" --prompt "a white dog"
+```
+
+Parameter description:
+- `--isize`: Input image size, recommended value is 256
+- `--model_dir`: Model directory
+- `-o`: Output image filename
+- `--prompt`: Description text; the model generates an image based on this description
+
+#### Image-to-Image
+```shell
+cd lcm-lora-sdv1-5-maixcam2
+python3 launcher.py --init_image ax620e_models/img2img-init.png --isize 256 --model_dir ax620e_models/ --seed 1 --prompt "Change to black clothes" -o "ax620e_img2img_axe.png"
+```
+
+Parameter description:
+- `--init_image`: Initial image; the model generates a new image based on this
+- `--isize`: Input image size, recommended value is 256
+- `--model_dir`: Model directory
+- `--seed`: Random seed, controls randomness during image generation
+- `-o`: Output image filename
+- `--prompt`: Description text; the model generates an image based on this description
+
+

docs/doc/en/mllm/dlm_lora_sdv1_5.md

@@ -124,8 +124,8 @@ items:
         label: InternVL Vision-Language Model
     -   file: mllm/vlm_qwen3.md
         label: Qwen3-VL Vision-Language Model
-    -   file: mllm/lm_lora_sdv1_5.md
-        label: LCM-LoRA-SDv1-5 Model
+    -   file: mllm/dlm_lora_sdv1_5.md
+        label: LCM-LoRA-SDv1-5 Image-Generation Model
     -   file: mllm/vlm_smolvlm.md
         label: SmolVLM Vision-Language Model
 

docs/doc/en/mllm/lm_lora_sdv1_5.md

@@ -0,0 +1,120 @@
+---
+title: MaixPy MaixCAM 运行 LCM-LoRA-SDv1-5 模型
+update:
+  - date: 2025-12-03
+    author: lxowalle
+    version: 1.0.0
+    content: 新增 LCM-LoRA-SDv1-5 代码和文档
+---
+
+## 支持的设备
+
+| 设备      | 是否支持 |
+| -------- | ------- |
+| MaixCAM2 | ✅ |
+| MaixCAM  | ❌ |
+
+
+## LCM-LoRA-SDv1-5 模型简介
+
+LCM-LoRA-SDv1-5 是一个支持文生图, 图生图的模型, 基于 StableDiffusion 1.5 LCM 项目. 我们可以通过这个模型来生成艺术创作的概念图, 只需要输入一段图片的描述文字, 模型便可以基于描述生成一张图片.
+
+## 在 MaixPy MaixCAM 运行 LCM-LoRA-SDv1-5 模型
+
+### 模型和下载地址
+
+默认系统`/root/models`目录下如果没有`LCM-LoRA-SDv1-5`模型，需要自行下载。
+
+  * 内存需求：CMM 内存 1GiB，内存解释请看[内存使用文档](../pro/memory.md)
+  * 下载地址：https://huggingface.co/sipeed/lcm-lora-sdv1-5-maixcam2
+
+下载方法参考[Qwen 文档](./llm_qwen.md) 里面的下载方法。
+
+### MaixPy 运行模型
+
+> 注意:必须要`MaixPy 4.12.3`以上版本才支持
+
+这里的示例展示了如何使用 MaixPy 运行 LCM-LoRA-SDv1-5 模型来实现文生文和图生图的功能
+
+```python
+from maix import sdv1_5
+
+model = sdv1_5.SDV1_5("/root/models/lcm-lora-sdv1-5-maixcam2/ax620e_models")
+model.init(img2img=True)
+model.refer(prompt="A white dog.", save_path="/root/text2img.jpg")
+model.refer(prompt="Replace the dog with a cat.", init_image_path="/root/text2img.jpg", seed=1, save_path="/root/img2img.jpg")
+
+model.deinit()
+```
+输出:
+![](../../assets/ldm_sdv1.5_img2img.jpg)
+
+说明:
+1. 执行文生文功能时, 需要定义一个`prompt`, 描述你的图片内容, 必须是英文输入, 生成的图片会保存在`save_path`指定的路径
+2. 执行图生图功能时, 需要定义一个`prompt`, 描述你要生成图片的内容, `init_image_path`指定初始图片, `seed`指定图片生成时的随机性, 生成的图片会保存在`save_path`指定的路径
+3. 由于`sdv1_5`依赖了一些比较大的python包, 因此在导入时会比较慢, 需要耐心等待. 开发时如果希望快速进入界面, 可以尝试使用`importlib`和`threading`库将加载模块的过程放到后台执行, 参考代码:
+```python
+from maix import time
+import importlib, threading
+
+class ModuleLoader():
+    def __load_module(self):
+        self.module = importlib.import_module(self.module_name)
+        self.load_ok = True
+        pass
+    def __init__(self, module_name: str):
+        self.module_name = module_name
+        self.module = None
+        self.load_ok = False
+        self.t = threading.Thread(target=self.__load_module)
+        self.t.start()
+    def try_get_module(self, block = True):
+        if self.load_ok:
+            return self.module
+        if block:
+            while not self.load_ok:
+                time.sleep_ms(100)
+            return self.module
+        else:
+            return None
+
+sdv1_5_loader = ModuleLoader("maix.sdv1_5")
+while True:
+    sdv1_5 = sdv1_5_loader.try_get_module(block=False)
+    if sdv1_5 is not None:
+        break
+    time.sleep_ms(1000)
+print(sdv1_5)
+```
+
+### 命令行运行模型
+
+请参考模型文件中的`launcher.py`来运行模型.
+
+#### 文生图
+```shell
+cd lcm-lora-sdv1-5-maixcam2
+python3 launcher.py --isize 256 --model_dir ax620e_models/ -o "ax620e_txt2img_axe.png" --prompt "a white dog"
+```
+
+参数说明:
+- `--isize`: 输入图片的尺寸, 推荐填写256
+- `--model_dir`: 模型目录
+- `-o`: 输出图片名称
+- `--prompt`: 描述文字, 模型基于这里的描述生成图片
+
+#### 图生图
+```shell
+cd lcm-lora-sdv1-5-maixcam2
+python3 launcher.py --init_image ax620e_models/img2img-init.png --isize 256 --model_dir ax620e_models/ --seed 1 --prompt "Change to black clothes" -o "ax620e_img2img_axe.png"
+```
+
+参数说明:
+- `--init_image`: 初始图片, 模型基于这个图片生成图片
+- `--isize`: 输入图片的尺寸, 推荐填写256
+- `--model_dir`: 模型目录
+- `--seed`: 随机种子, 代表图片生成时的随机性
+- `-o`: 输出图片名称
+- `--prompt`: 描述文字, 模型基于这里的描述生成图片
+
+

docs/doc/en/sidebar.yaml

@@ -125,8 +125,8 @@ items:
         label: InternVL 视觉语言模型
     -   file: mllm/vlm_qwen3.md
         label: Qwen3-VL 视觉语言模型
-    -   file: mllm/lm_lora_sdv1_5.md
-        label: LCM-LoRA-SDv1-5 模型
+    -   file: mllm/dlm_lora_sdv1_5.md
+        label: LCM-LoRA-SDv1-5 图像生成模型
     -   file: mllm/vlm_smolvlm.md
         label: SmolVLM 视觉语言模型