Color Canny ControlNet Model
These are ControlNet checkpoints trained on runwayml/stable-diffusion-v1-5, using fused color and canny edge as conditioning.
Fuente del modelo
- Tipo
- ControlNet
- Tamaño del archivo
- 689 MB
- Modelo base
- runwayml/stable-diffusion-v1-5
- Versión
- vdiffusion_pytorch_model
- Actualizado
- 6 oct 2026
- Descargas
- 33
- Fuente
- Hugging Face
Descripción de la fuente
Color-Canny CantrolNet
These are ControlNet checkpoints trained on runwayml/stable-diffusion-v1-5, using fused color and canny edge as conditioning.
You can find some example images in the following.
Examples
Color examples
prompt: a concept art of by Makoto Shinkai, a girl is standing in the middle of the sea
negative prompt: text, bad anatomy, blurry, (low quality, blurry) images_1)
prompt: a concept art of by Makoto Shinkai, a girl is standing in the middle of the sea
negative prompt: text, bad anatomy, blurry, (low quality, blurry) images_2)
prompt: a concept art of by Makoto Shinkai, a girl is standing in the middle of the grass
negative prompt: text, bad anatomy, blurry, (low quality, blurry) images_3)
Brightness examples
This model also can be used to control image brightness. The following images are generated with different brightness conditioning image and controlnet strength(0.5 ~ 0.7). images_4)
Limitations and Bias
- No strict control by input color
- Sometimes generate image with confusion When color description in prompt
Training
Dataset We train this model on laion-art dataset with 2.6m images, the processed dataset can be found in ghoskno/laion-art-en-colorcanny.
Training Details
-
Hardware: Google Cloud TPUv4-8 VM
-
Optimizer: AdamW
-
Train Batch Size: 4 x 4 = 16
-
Learning rate: 0.00001 constant
-
Gradient Accumulation Steps: 4
-
Resolution: 512
-
Train Steps: 36000
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 6 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- license: apache-2.0 datasets: - laion/laion-art language: - en library_name: diffusers pipeline_tag: image-to-image tags: - jax-diffusers-event base_model: runwayml/stable-diffusion-v1-5 --- # Color-Canny CantrolNet These are ControlNet checkpoints trained on runwayml/stable-diffusion-v1-5, using fused color and canny edge as conditioning. You can find some example images in the following. ## Examples #### Color examples **prompt**: a concept art of by Makoto Shinkai, a girl is standing in the middle of the sea **negative prompt**: text, bad anatomy, blurry, (low quality, blurry)  **prompt**: a concept art of by Makoto Shinkai, a girl is standing in the middle of the sea **negative prompt**: text, bad anatomy, blurry, (low quality, blurry)  **prompt**: a concept art of by Makoto Shinkai, a girl is standing in the middle of the grass **negative prompt**: text, bad anatomy, blurry, (low quality, blurry)  #### Brightness examples This model also can be used to control image brightness. The following images are generated with different brightness conditioning image and controlnet strength(0.5 ~ 0.7).  ## Limitations and Bias - No strict control by input color - Sometimes generate image with confusion When color description in prompt ## Training **Dataset** We train this model on [laion-art](https://huggingface.co/datasets/laion/laion-art) dataset with 2.6m images, the processed dataset can be found in [ghoskno/laion-art-en-colorcanny](https://huggingface.co/datasets/ghoskno/laion-art-en-colorcanny). **Training Details** - **Hardware**: Google Cloud TPUv4-8 VM - **Optimizer**: AdamW - **Train Batch Size**: 4 x 4 = 16 - **Learning rate**: 0.00001 constant - **Gradient Accumulation Steps**: 4 - **Resolution**: 512 - **Train Steps**: 36000
Source context: 33 downloads · 47 likes · Pipeline image-to-image · Library diffusers · Repo ghoskno/Color-Canny-Controlnet-model
Source context: 5 downloads · 47 likes · Pipeline image-to-image · Library diffusers · Repo ghoskno/Color-Canny-Controlnet-model
