add hr

models/RealESRGAN/RealESRGAN_x4plus.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4fa0d38905f75ac06eb49a7951b426670021be3018265fd191d2125df9d682f1
+size 67040989

models/RealESRGAN/RealESRGAN_x4plus_anime_6B.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f872d837d3c90ed2e05227bed711af5671a6fd1c9f7d7e91c911a61f155e99da
+size 17938799

models/RealESRGAN/realesr-general-x4v3.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8dc7edb9ac80ccdc30c3a5dca6616509367f05fbc184ad95b731f05bece96292
+size 4885111

predict.py

@@ -100,6 +100,7 @@ class Predictor(BasePredictor):
         cfg_scale: int = Input(description="cfg scale", default=8),
         width: int = Input(description="width", default=512),
         height: int = Input(description="height", default=768),
+        enable_hr: bool = Input(description="Generate high resoultion version", default=False),
         seed: int = Input(description="seed", default=-1),
     ) -> Path:
         """Run a single prediction on the model"""
@@ -114,6 +115,8 @@ class Predictor(BasePredictor):
             "cfg_scale": cfg_scale,
             "width": width,
             "height": height,
+            "enable_hr": enable_hr,
+            "hr_upscaler": "R-ESRGAN 4x+",
             "seed": seed,
         }
         p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)
@@ -122,38 +125,3 @@ class Predictor(BasePredictor):
         processed.images[0].save(fp=filename, format="PNG")
         # single_image_b64 = encode_pil_to_base64(processed.images[0]).decode('utf-8')
         return Path(filename)
-
-class PredictorOld(BasePredictor):
-    def setup(self):
-        """Load the model into memory to make running multiple predictions efficient"""
-        initialize()
-        self.shared = shared
-
-    def predict(
-        self,
-        prompt: str = Input(description="prompt en"),
-    ) -> Dict[str, Any]:
-        """Run a single prediction on the model"""
-        args = {
-            "do_not_save_samples": True,
-            "do_not_save_grid": True,
-            "outpath_samples": "./output",
-            "prompt": "lora:koreanDollLikeness_v15:0.66, best quality, ultra high res, (photorealistic:1.4), 1girl, beige sweater, black choker, smile, laughing, bare shoulders, solo focus, ((full body), (brown hair:1), looking at viewer",
-            "negative_prompt": "paintings, sketches, (worst quality:2), (low quality:2), (normal quality:2), lowres, normal quality, ((monochrome)), ((grayscale)), skin spots, acnes, skin blemishes, age spot, glans, (ugly:1.331), (duplicate:1.331), (morbid:1.21), (mutilated:1.21), (tranny:1.331), mutated hands, (poorly drawn hands:1.331), blurry, 3hands,4fingers,3arms, bad anatomy, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts,poorly drawn face,mutation,deformed",
-            "sampler_name": "DPM++ SDE Karras",
-            "steps": 20, # 25
-            "cfg_scale": 8,
-            "width": 512,
-            "height": 768,
-            "seed": -1,
-        }
-        if len(prompt) > 0:
-            print("get prompt from request: ", prompt)
-            args["prompt"] = prompt
-        p = StableDiffusionProcessingTxt2Img(sd_model=self.shared.sd_model, **args)
-        processed = process_images(p)
-        single_image_b64 = encode_pil_to_base64(processed.images[0]).decode('utf-8')
-        return {
-            "img_data": single_image_b64,
-            "parameters": processed.images[0].info.get('parameters', ""),
-        }