Update app.py

app.py

@@ -5,6 +5,7 @@ import numpy as np
 from PIL import Image
 from diffusers import AutoPipelineForImage2Image
 from diffusers.utils import load_image
+import math
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 pipe = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16) if torch.cuda.is_available() else AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo")
@@ -16,7 +17,9 @@ def resize(value,img):
     return img
 
 def infer(source_img, prompt, steps, seed, Strength):
-    generator = torch.Generator(device).manual_seed(seed)     
+    generator = torch.Generator(device).manual_seed(seed)  
+    if int(steps * Strength) < 1:
+        steps = math.ceil(1 / max(0.10, Strength))
     source_image = resize(512, source_img)
     source_image.save('source.png')
     image = pipe(prompt, image=source_image, strength=Strength, guidance_scale=0.0, num_inference_steps=steps).images[0]
@@ -25,7 +28,7 @@ def infer(source_img, prompt, steps, seed, Strength):
 gr.Interface(fn=infer, inputs=[
     gr.Image(sources=["upload", "webcam", "clipboard"], type="filepath", label="Raw Image."), 
     gr.Textbox(label = 'Prompt Input Text. 77 Token (Keyword or Symbol) Maximum'),
-    gr.Slider(2, 5, value = 2, step = 1, label = 'Number of Iterations'),
+    gr.Slider(1, 5, value = 2, step = 1, label = 'Number of Iterations'),
     gr.Slider(label = "Seed", minimum = 0, maximum = 987654321987654321, step = 1, randomize = True), 
-    gr.Slider(label='Strength', minimum = .5, maximum = 1, step = .05, value = .5)], 
+    gr.Slider(label='Strength', minimum = 0.0, maximum = 1, step = .05, value = .5)], 
     outputs='image', title = "Stable Diffusion XL Turbo Image to Image Pipeline CPU", description = "For more information on Stable Diffusion XL 1.0 see https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0 <br><br>Upload an Image (<b>MUST Be .PNG and 512x512 or 768x768</b>) enter a Prompt, or let it just do its Thing, then click submit. 10 Iterations takes about ~900-1200 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=5).launch()