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Parent(s):
9fcd704
Update app.py
Browse files
app.py
CHANGED
@@ -7,6 +7,24 @@ from diffusers import DiffusionPipeline, LCMScheduler
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from PIL import Image, ImageEnhance
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import io
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@spaces.GPU
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def generate_image(prompt, num_inference_steps, guidance_scale):
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model_id = "stabilityai/stable-diffusion-xl-base-1.0"
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@@ -60,39 +78,13 @@ def inpaint_image(prompt, init_image, mask_image, num_inference_steps, guidance_
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return image
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def generate_image_with_adapter(prompt, num_inference_steps, guidance_scale):
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0",
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variant="fp16",
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torch_dtype=torch.float32
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).to("cuda")
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# set scheduler
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
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# Load and fuse lcm lora
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pipe.load_lora_weights("latent-consistency/lcm-lora-sdxl", adapter_name="lcm")
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pipe.load_lora_weights("Pclanglais/Mickey-1928", weight_name="pytorch_lora_weights.safetensors", adapter_name="mickey")
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# Combine LoRAs
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pipe.set_adapters(["lcm", "mickey"], adapter_weights=[1.0, 0.8])
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pipe.fuse_lora()
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generator = torch.manual_seed(0)
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# Generate the image
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image = pipe(prompt=prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale, generator=generator).images[0]
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pipe.unfuse_lora()
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return image
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def modify_image(image, brightness, contrast):
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# Function to modify brightness and contrast
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image = Image.open(io.BytesIO(image))
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enhancer = ImageEnhance.Brightness(image)
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image = enhancer.enhance(brightness)
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enhancer = ImageEnhance.Contrast(image)
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image = enhancer.enhance(contrast)
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return image
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with gr.Blocks(gr.themes.Soft()) as demo:
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with gr.Row():
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image_output = gr.Image(label="Generated Image")
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from PIL import Image, ImageEnhance
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import io
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0",
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variant="fp16",
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torch_dtype=torch.float32
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).to("cuda")
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# set scheduler
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
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# Load and fuse lcm lora
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pipe.load_lora_weights("latent-consistency/lcm-lora-sdxl", adapter_name="lcm")
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pipe.load_lora_weights("Pclanglais/wiki-model", weight_name="pytorch_lora_weights.safetensors", adapter_name="mickey")
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# Combine LoRAs
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pipe.set_adapters(["lcm", "mickey"], adapter_weights=[1.0, 1.0])
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pipe.fuse_lora()
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@spaces.GPU
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def generate_image(prompt, num_inference_steps, guidance_scale):
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model_id = "stabilityai/stable-diffusion-xl-base-1.0"
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return image
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def generate_image_with_adapter(pipe, prompt, num_inference_steps, guidance_scale):
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generator = torch.manual_seed(0)
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# Generate the image
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image = pipe(prompt=prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale, generator=generator).images[0]
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return image
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with gr.Blocks(gr.themes.Soft()) as demo:
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with gr.Row():
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image_output = gr.Image(label="Generated Image")
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