Transformers
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controlnet
Inference Endpoints
Gerold Meisinger commited on
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4918ff0
1 Parent(s): 0b3513f

control-edgedrawing-cv480edpf-drop0-fp16-checkpoint-90000.safetensors

Browse files
README.md CHANGED
@@ -27,6 +27,7 @@ For usage see the model page on [Civitai.com](https://civitai.com/models/149740)
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  **Example**
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  sampler=UniPC steps=20 cfg=7.5 seed=0 batch=9 model: v1-5-pruned-emaonly.safetensors cherry-picked: 1/9
 
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  prompt: _a detailed high-quality professional photo of swedish woman standing in front of a mirror, dark brown hair, white hat with purple feather_
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64c0ec65a2ec8cb2f589233a/2PSWsmzLdHeVG-i67S7jF.png)
@@ -58,7 +59,7 @@ accelerate launch train_controlnet.py ^
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  # Versions
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- **v3 - control-edgedrawing-cv480edpf-drop0-fp16-checkpoint-45000**
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  Conditioning images generated with [edpf.py](https://gitlab.com/-/snippets/3601881) using [opencv-contrib-python::ximgproc::EdgeDrawing](https://docs.opencv.org/4.8.0/d1/d1c/classcv_1_1ximgproc_1_1EdgeDrawing.html).
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@@ -71,9 +72,13 @@ edges = ed.detectEdges(image)
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  edge_map = ed.getEdgeImage(edges)
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  ```
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- 45000 steps
 
 
 
 
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- **v2 - control-edgedrawing-default-noisy-drop0-fp16-checkpoint-40000**
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  Images converted with https://github.com/shaojunluo/EDLinePython
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@@ -94,9 +99,9 @@ Default settings are:
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  Trained for 40000 steps with default settings
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  => conditioning images are too noisy
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- **v1 - control-edgedrawing-default-drop50-fp16-checkpoint-40000**
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- Same as v1
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  Update: bug in algorithm produces too sparse images on default, see https://github.com/shaojunluo/EDLinePython/issues/4
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  **Example**
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  sampler=UniPC steps=20 cfg=7.5 seed=0 batch=9 model: v1-5-pruned-emaonly.safetensors cherry-picked: 1/9
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+
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  prompt: _a detailed high-quality professional photo of swedish woman standing in front of a mirror, dark brown hair, white hat with purple feather_
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64c0ec65a2ec8cb2f589233a/2PSWsmzLdHeVG-i67S7jF.png)
 
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  # Versions
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+ **Experiment 4 - control-edgedrawing-cv480edpf-drop0-fp16-checkpoint-90000**
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  Conditioning images generated with [edpf.py](https://gitlab.com/-/snippets/3601881) using [opencv-contrib-python::ximgproc::EdgeDrawing](https://docs.opencv.org/4.8.0/d1/d1c/classcv_1_1ximgproc_1_1EdgeDrawing.html).
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  edge_map = ed.getEdgeImage(edges)
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  ```
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+ 90000 steps (45000 steps on original, 45000 steps with left-right flipped images)
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+
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+ **Experiment 3 - control-edgedrawing-cv480edpf-drop0-fp16-checkpoint-45000**
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+
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+ see experiment 4. 45000 steps. This is version 0.1 on civitai.
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+ **Experiment 2 - control-edgedrawing-default-noisy-drop0-fp16-checkpoint-40000**
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  Images converted with https://github.com/shaojunluo/EDLinePython
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  Trained for 40000 steps with default settings
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  => conditioning images are too noisy
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+ **Experiment 1 - control-edgedrawing-default-drop50-fp16-checkpoint-40000**
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+ Same as experiment 2.
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  Update: bug in algorithm produces too sparse images on default, see https://github.com/shaojunluo/EDLinePython/issues/4
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control-edgedrawing-cv480edpf-drop0-fp16-checkpoint-90000.safetensors ADDED
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