das

app.py

@@ -34,10 +34,19 @@ def infer(source_img, prompt, negative_prompt, guide, steps, seed, Strength):
     source_image.save('source.png')
     image = pipe(prompt, negative_prompt=negative_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. Must Be .png"), gr.Textbox(label = 'Prompt Input Text. 77 Token (Keyword or Symbol) Maximum'), gr.Textbox(label='What you Do Not want the AI to generate.'),
-    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 2.1 Image to Image Pipeline CPU", description = "For more information on Stable Diffusion 2.1 see https://github.com/Stability-AI/stablediffusion <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()
+    
+gr.Interface(
+    fn=infer, 
+    inputs=[
+        gr.inputs.Image(type="filepath", label="Raw Image. Must Be .png"),  # Güncellenmiş kullanım
+        gr.Textbox(label='Prompt Input Text. 77 Token (Keyword or Symbol) Maximum'), 
+        gr.Textbox(label='What you Do Not want the AI to generate.'),
+        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 2.1 Image to Image Pipeline on CPU",
+    description="For more information on Stable Diffusion 2.1 see https://github.com/Stability-AI/stablediffusion"
+).launch()