init

README.md

@@ -1,13 +1,12 @@
 ---
-title: Stable Diffusion Demo
-emoji: 👀
-colorFrom: purple
-colorTo: purple
+title: Stable Diffusion Img2img CPU
+emoji: 🎨🌠
+colorFrom: green
+colorTo: indigo
 sdk: gradio
-sdk_version: 3.12.0
+sdk_version: 3.6
 app_file: app.py
 pinned: false
-license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,67 @@
+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")
+
+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)
+  return img
+
+
+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("Great sylvain ! Everything is working fine !")
+
+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 /> <img id='visitor-badge' alt='visitor badge' src='https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.stable-diffusion-img2img' style='display: inline-block'/></b></p>" 
+
+gr.Interface(fn=infer, inputs=[source_img,
+    "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)

requirements.txt

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+torch
+transformers
+scipy
+ftfy
+git+https://github.com/huggingface/diffusers

stable-diffusion-img2img

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+Subproject commit 102198819ddcbb3976017e23062f30eb069e752a