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Correct the command line arguments

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  1. README.md +4 -4
README.md CHANGED
@@ -26,7 +26,7 @@ huggingface-cli download Tencent-Hunyuan/HYDiT-ControlNet --local-dir ./ckpts/t2
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  huggingface-cli download Tencent-Hunyuan/Distillation-v1.1 ./pytorch_model_distill.pt --local-dir ./ckpts/t2i/model
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  # Quick start
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- python3 sample_controlnet.py --no-enhance --load-key distill --infer-steps 50 --control_type canny --prompt "在夜晚的酒店门前,一座古老的中国风格的狮子雕像矗立着,它的眼睛闪烁着光芒,仿佛在守护着这座建筑。背景是夜晚的酒店前,构图方式是特写,平视,居中构图。这张照片呈现了真实摄影风格,蕴含了中国雕塑文化,同时展现了神秘氛围" --condition_image_path controlnet/asset/input/canny.jpg --control_weight 1.0
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  ```
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  Examples of condition input and ControlNet results are as follows:
@@ -157,19 +157,19 @@ You can use the following command line for inference.
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  a. Using canny ControlNet during inference
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  ```bash
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- python3 sample_controlnet.py --no-enhance --load-key distill --infer-steps 50 --control_type canny --prompt "在夜晚的酒店门前,一座古老的中国风格的狮子雕像矗立着,它的眼睛闪烁着光芒,仿佛在守护着这座建筑。背景是夜晚的酒店前,构图方式是特写,平视,居中构图。这张照片呈现了真实摄影风格,蕴含了中国雕塑文化,同时展现了神秘氛围" --condition_image_path controlnet/asset/input/canny.jpg --control_weight 1.0
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  ```
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  b. Using pose ControlNet during inference
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  ```bash
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- python3 sample_controlnet.py --no-enhance --load-key distill --infer-steps 50 --control_type depth --prompt "在茂密的森林中,一只黑白相间的熊猫静静地坐在绿树红花中,周围是山川和海洋。背景是白天的森林,光线充足" --condition_image_path controlnet/asset/input/depth.jpg --control_weight 1.0
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  ```
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  c. Using depth ControlNet during inference
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  ```bash
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- python3 sample_controlnet.py --no-enhance --load-key distill --infer-steps 50 --control_type pose --prompt "一位亚洲女性,身穿绿色上衣,戴着紫色头巾和紫色围巾,站在黑板前。背景是黑板。照片采用近景、平视和居中构图的方式呈现真实摄影风格" --condition_image_path controlnet/asset/input/pose.jpg --control_weight 1.0
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  ```
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  huggingface-cli download Tencent-Hunyuan/Distillation-v1.1 ./pytorch_model_distill.pt --local-dir ./ckpts/t2i/model
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  # Quick start
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+ python3 sample_controlnet.py --no-enhance --load-key distill --infer-steps 50 --control-type canny --prompt "在夜晚的酒店门前,一座古老的中国风格的狮子雕像矗立着,它的眼睛闪烁着光芒,仿佛在守护着这座建筑。背景是夜晚的酒店前,构图方式是特写,平视,居中构图。这张照片呈现了真实摄影风格,蕴含了中国雕塑文化,同时展现了神秘氛围" --condition-image-path controlnet/asset/input/canny.jpg --control-weight 1.0
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  ```
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  Examples of condition input and ControlNet results are as follows:
 
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  a. Using canny ControlNet during inference
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  ```bash
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+ python3 sample_controlnet.py --no-enhance --load-key distill --infer-steps 50 --control-type canny --prompt "在夜晚的酒店门前,一座古老的中国风格的狮子雕像矗立着,它的眼睛闪烁着光芒,仿佛在守护着这座建筑。背景是夜晚的酒店前,构图方式是特写,平视,居中构图。这张照片呈现了真实摄影风格,蕴含了中国雕塑文化,同时展现了神秘氛围" --condition-image-path controlnet/asset/input/canny.jpg --control-weight 1.0
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  ```
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  b. Using pose ControlNet during inference
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  ```bash
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+ python3 sample_controlnet.py --no-enhance --load-key distill --infer-steps 50 --control-type depth --prompt "在茂密的森林中,一只黑白相间的熊猫静静地坐在绿树红花中,周围是山川和海洋。背景是白天的森林,光线充足" --condition-image-path controlnet/asset/input/depth.jpg --control-weight 1.0
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  ```
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  c. Using depth ControlNet during inference
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  ```bash
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+ python3 sample_controlnet.py --no-enhance --load-key distill --infer-steps 50 --control-type pose --prompt "一位亚洲女性,身穿绿色上衣,戴着紫色头巾和紫色围巾,站在黑板前。背景是黑板。照片采用近景、平视和居中构图的方式呈现真实摄影风格" --condition-image-path controlnet/asset/input/pose.jpg --control-weight 1.0
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  ```
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