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app.py
CHANGED
@@ -433,11 +433,7 @@ with gr.Blocks() as depth_map:
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gr.Markdown('''
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# π§βπ Depth Map Processor
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This tool desn't exist yet!
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When it's built it will let you input any image from your phone or computer and process it into a depth map image using a Stable Diffusion control net process.
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Hopefully it'll be working soon. Check out the example below for now!
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
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
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@@ -454,13 +450,7 @@ with gr.Blocks() as control_net:
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gr.Markdown('''
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# π§βπ Control Net Processor
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This tool desn't exist yet!
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When it's built it will let you input any image from your phone or computer and process it using any text prompt or combination of trained artist styles / concepts.
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Coming soon! If you want to play with normal control net without ahx artist concepts check out the link below.
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[control net](https://huggingface.co/spaces/hysts/ControlNet)
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''')
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@@ -476,17 +466,12 @@ with gr.Blocks() as inversion:
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This tool lets you train your own new models / concepts from any images you want that will appear automatically be added to the Beta Concepts and Advanced Prompting tabs!
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For now the tool lives on Google Colab, which is Google's free tool for using their GPU's. Someday it might live here on our Hugging Face Space, but the process is a little too demanding for our current resources.
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To train your own concept visit the link below and follow the instructions and be prepared to wait several hours.
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[textual inversion training tool](https://colab.research.google.com/drive/1FhOpcEjHT7EN53Zv9MFLQTytZp11wjqg#forceEdit=true&sandboxMode=true&scrollTo=ZajfEoWHKAr3)
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---
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Note that you will need a access_token to run this. You can request this on our discord or get your own free one at the link below.
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[hugging face access token](https://huggingface.co/docs/hub/security-tokens)
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''')
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@@ -500,13 +485,9 @@ with gr.Blocks() as dream_booth:
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gr.Markdown('''
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# π§βπ Dream Booth Concept Trainer
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This tool desn't exist yet!
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Coming soon! If you want to play with normal control net without ahx artist concepts check out the link below.
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[control net](https://huggingface.co/spaces/hysts/ControlNet)
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''')
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gr.Markdown('''
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# π§βπ Depth Map Processor
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+
This tool desn't exist yet! When it's built it will let you input any image from your phone or computer and process it into a depth map image using a Stable Diffusion control net process. Hopefully it'll be working soon. Check out the example below for now!
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
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
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gr.Markdown('''
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# π§βπ Control Net Processor
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+
This tool desn't exist yet! When it's built it will let you input any image from your phone or computer and process it using any text prompt or combination of trained artist styles / concepts. If you want to play with normal control net without ahx artist concepts check out the link below. [control net](https://huggingface.co/spaces/hysts/ControlNet)
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''')
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This tool lets you train your own new models / concepts from any images you want that will appear automatically be added to the Beta Concepts and Advanced Prompting tabs!
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+
For now the tool lives on Google Colab, which is Google's free tool for using their GPU's. Someday it might live here on our Hugging Face Space, but the process is a little too demanding for our current resources. To train your own concept visit the link below and follow the instructions and be prepared to wait several hours.
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[textual inversion training tool](https://colab.research.google.com/drive/1FhOpcEjHT7EN53Zv9MFLQTytZp11wjqg#forceEdit=true&sandboxMode=true&scrollTo=ZajfEoWHKAr3)
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Note that you will need a access_token to run this. You can request this on our discord or get your own free one at the link below. [hugging face access token](https://huggingface.co/docs/hub/security-tokens)
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''')
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gr.Markdown('''
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# π§βπ Dream Booth Concept Trainer
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This tool desn't exist yet! When it's built it will let you train concepts using a process distinct from our current concept training tool which uses textual inversion training. To read more about Dream Booth check out the link below!
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[dream booth](https://huggingface.co/spaces/multimodalart/dreambooth-training)
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''')
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