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RealESRGAN_x2plus.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:49fafd45f8fd7aa8d31ab2a22d14d91b536c34494a5cfe31eb5d89c2fa266abb
+size 67061725

RealESRGAN_x4plus (1).pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4fa0d38905f75ac06eb49a7951b426670021be3018265fd191d2125df9d682f1
+size 67040989

handler.py

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+from base64 import b64encode, b64decode
+from io import BytesIO
+from pathlib import Path
+
+import numpy as np
+from basicsr.archs.rrdbnet_arch import RRDBNet
+from PIL import Image
+from realesrgan import RealESRGANer
+
+
+class EndpointHandler:
+    def __init__(self, path=""):
+        model = RRDBNet(num_in_ch=3, num_out_ch=3)
+        self.upsampler = RealESRGANer(
+            scale=4,
+            model_path=str(Path(path) / "RealESRGAN_x4plus.pth"),
+            model=model,
+            tile=0,
+            pre_pad=0,
+            half=True,
+        )
+
+    def __call__(self, data):
+        """
+        Args:
+            data (:obj:):
+                includes the input data and the parameters for the inference.
+        Return:
+            A :obj:`dict`:. base64 encoded image
+        """
+        image = data.pop("inputs", data)
+
+        # This lets us pass local images as well while developing
+        if isinstance(image, str):
+            image = Image.open(BytesIO(b64decode(image)))
+        elif isinstance(image, bytes):
+            image = Image.open(BytesIO(image))
+
+        image = np.array(image)
+        image = image[:, :, ::-1]  # RGB -> BGR
+        image, _ = self.upsampler.enhance(image, outscale=4)
+        image = image[:, :, ::-1]  # BGR -> RGB
+        image = Image.fromarray(image)
+
+        # Turn output image into bytestr
+        buffered = BytesIO()
+        image.save(buffered, format="PNG")
+        img_bytes = b64encode(buffered.getvalue())
+        img_str = img_bytes.decode()
+
+        return {"image": img_str}

requirements.txt

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+realesrgan==0.3.0