Upload feifeiimgtoimg.py

feifeilib/feifeiimgtoimg.py

@@ -10,9 +10,9 @@ from diffusers.utils import load_image
 
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
-pipe = FluxImg2ImgPipeline.from_pretrained("aifeifei798/shuttle-3-diffusion",
+img_pipe = FluxImg2ImgPipeline.from_pretrained("aifeifei798/shuttle-3-diffusion",
                                            torch_dtype=dtype)
-pipe = pipe.to(device)
+img_pipe = img_pipe.to(device)
 MAX_SEED = np.iinfo(np.int32).max
 
 @spaces.GPU()
@@ -22,14 +22,14 @@ def feifeiimgtoimg(img_in_result,
     seed = random.randint(0, MAX_SEED)
     generator = torch.Generator().manual_seed(seed)
     init_image = load_image(img_in_result)
-    images = pipe(prompt="",
-                  prompt_2=prompt,
-                  image=init_image,
-                  width=896,
-                  height=1152,
-                  num_inference_steps=4,
-                  strength=0.95,
-                  generator=generator,
-                  utput_type="pil",
-                  guidance_scale=3.5).images[0]
+    images = img_pipe(prompt="",
+                      prompt_2=prompt,
+                      image=init_image,
+                      width=896,
+                      height=1152,
+                      num_inference_steps=4,
+                      strength=0.95,
+                      generator=generator,
+                      utput_type="pil",
+                      guidance_scale=3.5).images[0]
     return images