add sd1.5

lama_cleaner/model/sd.py

@@ -7,8 +7,6 @@ import torch
 from diffusers import PNDMScheduler, DDIMScheduler, LMSDiscreteScheduler
 from loguru import logger
 
-from lama_cleaner.helper import norm_img
-
 from lama_cleaner.model.base import InpaintModel
 from lama_cleaner.schema import Config, SDSampler
 
@@ -38,12 +36,22 @@ from lama_cleaner.schema import Config, SDSampler
 #     mask = torch.from_numpy(mask)
 #     return mask
 
+class CPUTextEncoderWrapper:
+    def __init__(self, text_encoder):
+        self.text_encoder = text_encoder.to(torch.device('cpu'), non_blocking=True)
+        self.text_encoder = self.text_encoder.to(torch.float32, non_blocking=True)
+
+    def __call__(self, x):
+        input_device = x.device
+        return [self.text_encoder(x.to(self.text_encoder.device))[0].to(input_device)]
+
+
 class SD(InpaintModel):
-    pad_mod = 64  # current diffusers only support 64 https://github.com/huggingface/diffusers/pull/505
+    pad_mod = 8  # current diffusers only support 64 https://github.com/huggingface/diffusers/pull/505
     min_size = 512
 
     def init_model(self, device: torch.device, **kwargs):
-        from .sd_pipeline import StableDiffusionInpaintPipeline
+        from diffusers.pipelines.stable_diffusion import StableDiffusionInpaintPipeline
 
         model_kwargs = {"local_files_only": kwargs['sd_run_local']}
         if kwargs['sd_disable_nsfw']:
@@ -65,8 +73,7 @@ class SD(InpaintModel):
 
         if kwargs['sd_cpu_textencoder']:
             logger.info("Run Stable Diffusion TextEncoder on CPU")
-            self.model.text_encoder = self.model.text_encoder.to(torch.device('cpu'), non_blocking=True)
-            self.model.text_encoder = self.model.text_encoder.to(torch.float32, non_blocking=True )
+            self.model.text_encoder = CPUTextEncoderWrapper(self.model.text_encoder)
 
         self.callback = kwargs.pop("callback", None)
 
@@ -99,7 +106,6 @@ class SD(InpaintModel):
             )
         elif config.sd_sampler == SDSampler.pndm:
             PNDM_kwargs = {
-                "tensor_format": "pt",
                 "beta_schedule": "scaled_linear",
                 "beta_start": 0.00085,
                 "beta_end": 0.012,
@@ -124,15 +130,19 @@ class SD(InpaintModel):
             k = 2 * config.sd_mask_blur + 1
             mask = cv2.GaussianBlur(mask, (k, k), 0)[:, :, np.newaxis]
 
+        _kwargs = {
+            self.image_key: PIL.Image.fromarray(image),
+        }
+
         output = self.model(
             prompt=config.prompt,
-            init_image=PIL.Image.fromarray(image),
             mask_image=PIL.Image.fromarray(mask[:, :, -1], mode="L"),
             strength=config.sd_strength,
             num_inference_steps=config.sd_steps,
             guidance_scale=config.sd_guidance_scale,
             output_type="np.array",
             callback=self.callback,
+            **_kwargs
         ).images[0]
 
         output = (output * 255).round().astype("uint8")
@@ -185,7 +195,9 @@ class SD(InpaintModel):
 
 class SD14(SD):
     model_id_or_path = "CompVis/stable-diffusion-v1-4"
+    image_key = "init_image"
 
 
 class SD15(SD):
-    model_id_or_path = "CompVis/stable-diffusion-v1-5"
+    model_id_or_path = "runwayml/stable-diffusion-inpainting"
+    image_key = "image"