Update app.py

app.py

@@ -4,6 +4,7 @@ import numpy as np
 from PIL import Image
 from datasets import load_dataset
 from diffusers import StableDiffusionImg2ImgPipeline
+
 device = "cuda" if torch.cuda.is_available() else "cpu"
 pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-2", torch_dtype=torch.float16, revision="fp16") if torch.cuda.is_available() else StableDiffusionImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-2")
 pipe = pipe.to(device)
@@ -20,13 +21,9 @@ def infer(source_img, prompt, guide, steps, seed, Strength):
     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=[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 = .5)
-    ], outputs='image', title = "Stable Diffusion 2.0 Image to Image Pipeline CPU", description = "For more information on Stable Diffusion 2.0 see https://github.com/Stability-AI/stablediffusion <br><br>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 ~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()
+gr.Interface(fn=infer, inputs=[gr.Image(source="upload", type="filepath", label="Raw Image. <b>Must Be .png"), gr.Textbox(label = 'Prompt Input Text. <b>77 Token (Keyword or Symbol) Maximum'),
+    gr.Slider(2, 15, value = 7, label = 'Guidance Scale'),
+    gr.Slider(1, 25, value = 10, step = 1, label = 'Number of Iterations'),
+    gr.Slider(label = "Seed", minimum = 0, maximum = 987654321987654321, step = 1, randomize = True), 
+    gr.Slider(label='Strength', minimum = 0, maximum = 1, step = .05, value = .5)], 
+    outputs='image', title = "Stable Diffusion 2.0 Image to Image Pipeline CPU", description = "For more information on Stable Diffusion 2.0 see https://github.com/Stability-AI/stablediffusion <br><br>Upload an Image (<b>MUST Be .PNG and 512x512 or 768x768) 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()