import os import shutil import torch import gradio as gr MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD') from PIL import Image,ImageFont,ImageDraw from gradio.mix import Series #from io import BytesIO from diffusers import StableDiffusionImg2ImgPipeline YOUR_TOKEN=MY_SECRET_TOKEN device="cuda" if torch.cuda.is_available() else "cpu" pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", use_auth_token=YOUR_TOKEN) pipe.to(device) #draw an image based off of user's text input def drawImage(text, text_size, prompt, strength, guidance_scale): #(text, text_size, font) out = Image.new("RGB", (512, 512), (0, 0, 0)) #add some code here to move font to font-directory font = './font-directory/DimpleSans-Regular.otf' fnt = ImageFont.truetype(font, int(text_size)) d = ImageDraw.Draw(out) d.multiline_text((16, 64), text, font=fnt, fill=(255, 255, 255)) #init_image = out out.save('initImage.png') images = [] images = pipe(prompt=prompt, image=out, strength=strength, guidance_scale=guidance_scale).images #images[0].save = ("image.png") #images = [] #images.append(out) #out.show() return images[0] #def newImage(image, prompt): #return images test #drawImage = gr.Interface(fn=drawImage, inputs=gr.Textbox(placeholder="shift + enter for new line",label="what do you want to say?"),outputs="image") #newImage = gr.Interface(fn=newImage,inputs=[gr.Textbox(placeholder="prompt",label="how does your message look and feel?")],outputs="image") #demo = gr.Series(drawImage,newImage) #blocks = gr.Blocks() demo = gr.Interface( title="Text Decorator", description="Note: This will be very slow since it is running on CPU.", #description="Save or screenshot your creations and share on https://forms.gle/qhzc7nfX7VGwBco96 ⚡️ (Note: I've upgraded the hardware today from 7-9pm so that it runs faster, if you visit this link in the future, it will be slower.)", ##theme='huggingface', #css=""" #body {font-family: system-ui, Helvetica, Arial, sans-serif} #""", fn=drawImage, inputs=[ gr.Textbox(placeholder="shift + enter for new line",label="what do you want to say?"), ##"file" gr.Number(label="text size",value=240), gr.Textbox(placeholder="eg. imagery, art style, materials, emotions",label="how does your message look and feel?"), #figure out models in series gr.Slider(label="strength (how much noise will be added to the input image)",minimum=0, maximum=1, step=0.01, value=0.7), gr.Slider(label="guidance scale (how much the image generation follows the prompt)",value=15, maximum=20), ], outputs="image") #with blocks (css=".gradio-container {background-color: red}") as demo: #fn=drawImage, #inputs=[ #gr.Textbox(placeholder="shift + enter for new line",label="what do you want to say?"), ##"file" #gr.Number(label="text size",value=240), #gr.Textbox(placeholder="eg. imagery, art style, materials, emotions",label="how does your message look and feel?"), #figure out models in series #gr.Slider(label="strength (how much noise will be added to the input image)",minimum=0, maximum=1, step=0.01, value=0.7), #gr.Slider(label="guidance scale (how much the image generation follows the prompt)",value=15, maximum=20), #], #outputs="image" demo.launch()