Create app.py

app.py

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+import gradio as gr
+#import torch
+#from torch import autocast // only for GPU
+
+from PIL import Image
+
+import os
+MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD')
+
+from diffusers import StableDiffusionPipeline
+#from diffusers import StableDiffusionImg2ImgPipeline
+
+print("start generating")
+
+YOUR_TOKEN=MY_SECRET_TOKEN
+
+device="cpu"
+
+pipe = StableDiffusionPipeline.from_pretrained("AkiKagura/mkgen-diffusion", use_auth_token=YOUR_TOKEN)
+pipe.to(device)
+
+gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[2], height="auto")
+
+def infer(prompt): 
+    
+    #image = pipe(prompt, init_image=init_image)["sample"][0]
+    images_list = pipe([prompt] * 4)
+    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("okay")
+
+title="Marco Generation"
+description="Use 'mkmk woman' to get Marco pics. <br />Warning: Slow process... ~5/10 min inference time. <b>NSFW filter enabled.</b>" 
+
+gr.Interface(fn=infer, inputs="text", outputs=gallery,title=title,description=description).queue(max_size=10).launch(enable_queue=True)