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import gradio as gr
from PIL import Image
import base64
import io
import glob
import cv2
import numpy as np
import torch
from controlnet_aux import HEDdetector
from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
def predict(sketch, description):
# Convert sketch to PIL image
sketch_pil = Image.fromarray(sketch)
hed = HEDdetector.from_pretrained('lllyasviel/Annotators')
image = hed(sketch_pil, scribble=True)
model_id = "runwayml/stable-diffusion-v1-5"
controlnet_id = "lllyasviel/sd-controlnet-scribble"
# Load ControlNet model
controlnet = ControlNetModel.from_pretrained(controlnet_id)
# Create pipeline with ControlNet model
pipe = StableDiffusionControlNetPipeline.from_pretrained(model_id, controlnet=controlnet)
# Use improved scheduler
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
# Enable smart CPU offloading and memory efficient attention
# pipe.enable_model_cpu_offload()
# pipe.enable_xformers_memory_efficient_attention()
# Move pipeline to GPU
# pipe = pipe.to("cuda")
result = pipe(description, image, num_inference_steps=10).images[0]
return result
with gr.Blocks() as iface:
# Define sketchpad with custom size and stroke width
sketchpad = gr.Sketchpad(shape=(400, 300), brush_radius=5, label="Sketchpad- Draw something")
txt= gr.Textbox(lines=3, label="Description - Describe your sketch with style")
im = gr.Image(label="Output Image", interactive=False)
button = gr.Button(value="Submit")
button.click(predict, inputs=[sketchpad, txt], outputs=im)
flag= gr.CSVLogger()
flag.setup([sketchpad, txt, im], "flagged_data_points")
button_flag = gr.Button(value="Flag")
button_flag.click(lambda *args: flag.flag(args), [sketchpad, txt, im], None, preprocess=False)
# iface = gr.Interface(fn=predict, inputs=[sketchpad, "text"], outputs=im, live=False, title="Sketch2Image")
## get all the file path from flagged/sketch folder into a list
sketch_path = glob.glob("flagged/sketch/*.png")
# gr.Examples(examples = list(map(lambda x: [x ,"draw in the style of crayon by kids"], sketch_path)), inputs=[sketchpad,txt], outputs=im, fn=predict, cache_examples=True)
iface.launch()
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