update readme

README.md

@@ -9,31 +9,37 @@ Note the input image is suppose to be **white background**.
 import torch 
 import numpy as np 
 from PIL import Image 
-from pipeline_img2mvimg import StableDiffusionImage2MVCustomPipeline
+from pipeline import StableDiffusionImage2MVCustomPipeline
 
 
 pipe = StableDiffusionImage2MVCustomPipeline.from_pretrained( 
-    "Luffuly/unique3d-mv-variation-diffuser",  
+    ".", 
+    # "Luffuly/unique3d-mv-variation-diffuser", 
     torch_dtype=torch.float16, 
-    trust_remote_code=True 
+    trust_remote_code=True,  
+    class_labels=torch.tensor(range(4)),
 ).to("cuda")
 
+seed = -1    
+generator = torch.Generator(device='cuda').manual_seed(-1)
 
-image = Image.open('image.png').convert("RGB")
 
+image = Image.open('/media/mbzuai/Tingting/unique3d-diffuser/hao.png').convert("RGB")
 forward_args = dict(
     width=256,
     height=256,
-    width_cond=256,
-    height_cond=256,  
     num_images_per_prompt=4, 
-    num_inference_steps=50,  
+    num_inference_steps=50, 
+    width_cond=256,
+    height_cond=256, 
+    generator=generator,
     guidance_scale=1.5,  
 ) 
 
 out = pipe(image, **forward_args).images
 rgb_np = np.hstack([np.array(img) for img in out])
-Image.fromarray(rgb_np).save(f"mvimg.png")
+Image.fromarray(rgb_np).save(f"test.png")
+
 ```
 
 ## Image-to-Normal