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app.py

@@ -1,68 +1,35 @@
+import streamlit as st
 import gradio as gr
 import torch
-#from torch import autocast // only for GPU
-
 from PIL import Image
 import numpy as np
 from io import BytesIO
-import os
-MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD')
-
-#from diffusers import StableDiffusionPipeline
 from diffusers import StableDiffusionImg2ImgPipeline
 
-print("hello sylvain")
-
-YOUR_TOKEN=MY_SECRET_TOKEN
-
 device="cpu"
 
-#prompt_pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token=YOUR_TOKEN)
-#prompt_pipe.to(device)
-
-img_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", use_auth_token=YOUR_TOKEN)
-img_pipe.to(device)
-
-source_img = gr.Image(source="upload", type="filepath", label="init_img | 512*512 px")
-gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[1], height="auto")
+pipe = StableDiffusionImg2ImgPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token = st.secrets['USER_TOKEN'])
+pipe.to(device)
 
 def resize(value,img):
-  #baseheight = value
   img = Image.open(img)
-  #hpercent = (baseheight/float(img.size[1]))
-  #wsize = int((float(img.size[0])*float(hpercent)))
-  #img = img.resize((wsize,baseheight), Image.Resampling.LANCZOS)
-  img = img.resize((value,value), Image.Resampling.LANCZOS)
+  img = img.resize((value,value))
   return img
 
-
-def infer(source_img, prompt, guide, steps, seed, strength): 
-    generator = torch.Generator('cpu').manual_seed(seed)
-    
+def infer(source_img, prompt, guide, steps, seed, Strength): 
+    generator = torch.Generator("cpu").manual_seed(seed)     
     source_image = resize(512, source_img)
     source_image.save('source.png')
-    
-    images_list = img_pipe([prompt] * 1, init_image=source_image, strength=strength, guidance_scale=guide, num_inference_steps=steps)
-    images = []
-    safe_image = Image.open(r"unsafe.png")
-    
-    for i, image in enumerate(images_list["images"]):
-        if(images_list["nsfw_content_detected"][i]):
-            images.append(safe_image)
-        else:
-            images.append(image)    
-    return images
-
-print("Running properly")
-print(MY_SECRET_TOKEN)
-
-title="Img2Img Stable Diffusion CPU"
-description="<p style='text-align: center;'>Img2Img Stable Diffusion example using CPU and HF token. <br />Warning: Slow process... ~5/10 min inference time. <b>NSFW filter enabled. <br /> </b></p>" 
+    image = pipe([prompt], init_image=source_image, strength=Strength, guidance_scale=guide, num_inference_steps=steps).images[0]
+    return image
 
-gr.Interface(fn=infer, inputs=[source_img,
-    "text",
+gr.Interface(fn=infer, inputs=[gr.Image(source="upload", type="filepath", label="Raw Image"), gr.Textbox(label = 'Prompt Input Text'),
     gr.Slider(2, 15, value = 7, label = 'Guidence Scale'),
     gr.Slider(10, 50, value = 25, step = 1, label = 'Number of Iterations'),
-    gr.Slider(label = "Seed", minimum = 0, maximum = 2147483647, step = 1, randomize = True),
-    gr.Slider(label='Strength', minimum = 0, maximum = 1, step = .05, value = .75)],
-    outputs=gallery,title=title,description=description, allow_flagging="manual", flagging_dir="flagged").queue(max_size=100).launch(enable_queue=True)
+    gr.Slider(
+        label = "Seed",
+        minimum = 0,
+        maximum = 2147483647,
+        step = 1,
+        randomize = True), gr.Slider(label='Strength', minimum = 0, maximum = 1, step = .05, value = .5)
+    ], outputs='image', title = "Stable Diffusion Image to Image Pipeline CPU", description = "Upload an Image (must be .PNG and 512x512-2048x2048) enter a Prompt, or let it just do its Thing, then click submit. 10 Iterations takes about 300 seconds currently. For more informationon about Stable Diffusion or Suggestions for prompts, keywords, artists or styles see https://github.com/Maks-s/sd-akashic", article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").queue(max_size=10).launch(enable_queue=True, debug=True)

requirements.txt

@@ -1,6 +1,6 @@
-torch
-transformers
-scipy
-ftfy
 accelerate
-git+https://github.com/huggingface/diffusers
+diffusers
+ftfy
+scipy
+transformers
+torch