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README.md

@@ -1,13 +1,11 @@
----
-title: FFusion.AI Beta Playground
-emoji: 👀
-colorFrom: pink
+---
+title: FFusion.AI -beta- Playground
+emoji: 😻
+colorFrom: purple
 colorTo: pink
 sdk: gradio
-sdk_version: 3.35.2
+sdk_version: 3.29.0
 app_file: app.py
-pinned: false
+pinned: true
 license: creativeml-openrail-m
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---

app.py

@@ -1,3 +1,109 @@
 import gradio as gr
+import numpy as np
+from diffusers import StableDiffusionPipeline, DDPMScheduler, DDIMScheduler, PNDMScheduler, LMSDiscreteScheduler, EulerDiscreteScheduler, EulerAncestralDiscreteScheduler, DPMSolverMultistepScheduler
+import torch
+import PIL.Image
+import datetime
 
-gr.Interface.load("models/FFusion/FFusion-BaSE").launch()
+# Check environment
+print(f"Is CUDA available: {torch.cuda.is_available()}")
+print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
+
+device = "cuda"
+
+schedulers = {
+    "DDPMScheduler": DDPMScheduler,
+    "DDIMScheduler": DDIMScheduler,
+    "PNDMScheduler": PNDMScheduler,
+    "LMSDiscreteScheduler": LMSDiscreteScheduler,
+    "EulerDiscreteScheduler": EulerDiscreteScheduler,
+    "EulerAncestralDiscreteScheduler": EulerAncestralDiscreteScheduler,
+    "DPMSolverMultistepScheduler": DPMSolverMultistepScheduler
+}
+
+class Model:
+    def __init__(self, modelID, schedulerName):
+        self.modelID = modelID
+        self.pipe = StableDiffusionPipeline.from_pretrained(modelID, torch_dtype=torch.float16)
+        self.pipe = self.pipe.to(device)
+        self.pipe.scheduler = schedulers[schedulerName].from_config(self.pipe.scheduler.config)
+        self.pipe.enable_xformers_memory_efficient_attention()
+
+    def process(self, 
+                prompt: str, 
+                negative_prompt: str,
+                guidance_scale:int = 6,
+                num_images:int = 1,
+                num_steps:int = 35):
+        seed = np.random.randint(0, np.iinfo(np.int32).max)
+        generator = torch.Generator(device).manual_seed(seed)
+        now = datetime.datetime.now()
+        print(now)
+        print(self.modelID)
+        print(prompt)
+        print(negative_prompt)
+        with torch.inference_mode():
+            images = self.pipe(prompt=prompt,
+                         negative_prompt=negative_prompt,
+                         guidance_scale=guidance_scale,
+                         num_images_per_prompt=num_images,
+                         num_inference_steps=num_steps,
+                         generator=generator,
+                         height=768, 
+                         width=768).images  
+        images = [PIL.Image.fromarray(np.array(img)) for img in images]
+        return images
+
+
+
+
+                    
+def generateImage(prompt, n_prompt, modelName, schedulerName):
+    images = models[modelName].process(prompt, n_prompt)
+    images = [np.array(img) for img in images]
+    return images[0]  # Return the first image
+
+def create_demo():
+    # Settings are defined here
+    prompt = gr.inputs.Textbox(label='Prompt',default='a sprinkled donut sitting on top of a table, blender donut tutorial, colorful hyperrealism, everything is made of candy, hyperrealistic digital painting, covered in sprinkles and crumbs, vibrant colors hyper realism, colorful smoke explosion background')
+    n_prompt = gr.inputs.Textbox(
+        label='Negative Prompt',
+        default='(disfigured), ((bad art)), ((deformed)), ((extra limbs)), (((duplicate))), ((morbid)), ((mutilated)), out of frame, extra fingers, mutated hands, poorly drawn eyes, ((poorly drawn hands)), ((poorly drawn face)), (((mutation))), ((ugly)), blurry, ((bad anatomy)), (((bad proportions))), cloned face, body out of frame, out of frame, bad anatomy, gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), (fused fingers), (too many fingers), (((long neck))), Deformed, blurry'
+    )
+    modelName = gr.inputs.Dropdown(choices=list(models.keys()), 
+                                   label="FFusion Test Model",
+                                   default=list(models.keys())[0])  # Set the default model
+    schedulerName = gr.inputs.Dropdown(choices=list(schedulers.keys()), 
+                                       label="Scheduler",
+                                       default=list(schedulers.keys())[0])  # Set the default scheduler
+    inputs = [prompt, n_prompt, modelName, schedulerName]
+
+    # Images are displayed here
+    result = gr.outputs.Image(label='Output', type="numpy")
+
+    # Define the function to run when the button is clicked
+    def run(prompt, n_prompt, modelName, schedulerName):
+        return generateImage(prompt, n_prompt, modelName, schedulerName)
+
+    # Create the interface
+    iface = gr.Interface(
+    fn=run,
+    inputs=inputs,
+    outputs=result,
+    layout=[
+        gr.Markdown("### FFusion.AI - beta Playground"),
+        inputs,
+        result
+    ]
+)
+
+    return iface
+
+if __name__ == '__main__':
+    models = {
+        "FFUSION.ai-768-BaSE": Model("FFusion/FFusion-BaSE", list(schedulers.keys())[0]),
+        "FFUSION.ai-v2.1-768-BaSE-alpha-preview": Model("FFusion/di.FFUSION.ai-v2.1-768-BaSE-alpha", list(schedulers.keys())[0]),
+    "FFusion.ai.Beta-512": Model("FFusion/di.ffusion.ai.Beta512", list(schedulers.keys())[0])
+    }
+    demo = create_demo()
+    demo.launch()

requirements.txt

@@ -0,0 +1,10 @@
+--extra-index-url https://download.pytorch.org/whl/cu113
+torch
+accelerate==0.18.0
+diffusers==0.16.0
+gradio==3.30.0
+safetensors==0.3.0
+torchvision==0.15.1
+transformers==4.28.1
+xformers==0.0.18
+numpy