e

app.py

@@ -1,44 +1,32 @@
 import gradio as gr
-import pandas as pd
 import torch
-import numpy as np
 from PIL import Image
-from diffusers import DiffusionPipeline
-from huggingface_hub import login
-import gradio as gr
-import torch
-import numpy as np
-from PIL import Image
-from datasets import load_dataset
-from diffusers import StableDiffusionImg2ImgPipeline
-
-import torch
 from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 
 model_id = "stabilityai/stable-diffusion-2-1"
 
 device = "cpu"
 # DPM-Solver++ scheduler'ını kullan, torch_dtype belirtme
-pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
+pipe = StableDiffusionPipeline.from_pretrained(model_id)
 pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
 pipe = pipe.to(device)
 
-def resize(value,img):
-    img = Image.open(img)
-    img = img.resize((value,value))
+def resize(value, img_path):
+    img = Image.open(img_path)
+    img = img.resize((value, value))
     return img
 
 def infer(source_img, prompt, negative_prompt, guide, steps, seed, Strength):
-    generator = torch.Generator(device).manual_seed(seed)     
+    generator = torch.Generator(device).manual_seed(seed)
     source_image = resize(768, source_img)
     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]
+    image = pipe(prompt, negative_prompt=negative_prompt, init_image=source_image, strength=Strength, guidance_scale=guide, num_inference_steps=steps, generator=generator).images[0]
     return image
-    
+
 gr.Interface(
     fn=infer, 
     inputs=[
-        gr.inputs.Image(type="filepath", label="Raw Image. Must Be .png"),  # Güncellenmiş kullanım
+        gr.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'),
@@ -46,7 +34,7 @@ gr.Interface(
         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",
+    outputs=gr.Image(type="pil"), 
+    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()
+).launch()