feat(api): use ONNX for Real ESRGAN v3 model

api/onnx_web/chain/upscale_resrgan.py

@@ -37,16 +37,6 @@ def load_resrgan(
     if not path.isfile(model_path):
         raise Exception("Real ESRGAN model not found at %s" % model_path)
 
-    if x4_v3_tag in model_file:
-        # the x4-v3 model needs a different network
-        model = SRVGGNetCompact(
-            num_in_ch=3,
-            num_out_ch=3,
-            num_feat=64,
-            num_conv=32,
-            upscale=4,
-            act_type="prelu",
-        )
     elif params.format == "onnx":
         # use ONNX acceleration, if available
         model = OnnxNet(
@@ -56,14 +46,25 @@ def load_resrgan(
             sess_options=device.sess_options(),
         )
     elif params.format == "pth":
-        model = RRDBNet(
-            num_in_ch=3,
-            num_out_ch=3,
-            num_feat=64,
-            num_block=23,
-            num_grow_ch=32,
-            scale=params.scale,
-        )
+        if x4_v3_tag in model_file:
+            # the x4-v3 model needs a different network
+            model = SRVGGNetCompact(
+                num_in_ch=3,
+                num_out_ch=3,
+                num_feat=64,
+                num_conv=32,
+                upscale=4,
+                act_type="prelu",
+            )
+        else:
+            model = RRDBNet(
+                num_in_ch=3,
+                num_out_ch=3,
+                num_feat=64,
+                num_block=23,
+                num_grow_ch=32,
+                scale=params.scale,
+            )
     else:
         raise Exception("unknown platform %s" % params.format)
 

api/onnx_web/onnx/__init__.py

@@ -1 +1 @@
-from .onnx_net import OnnxImage, OnnxNet
+from .onnx_net import OnnxTensor, OnnxNet

api/onnx_web/onnx/onnx_net.py

@@ -8,7 +8,7 @@ from onnxruntime import InferenceSession, SessionOptions
 from ..utils import ServerContext
 
 
-class OnnxImage:
+class OnnxTensor:
     def __init__(self, source) -> None:
         self.source = source
         self.data = self
@@ -57,8 +57,10 @@ class OnnxNet:
     def __call__(self, image: Any) -> Any:
         input_name = self.session.get_inputs()[0].name
         output_name = self.session.get_outputs()[0].name
-        output = self.session.run([output_name], {input_name: image.cpu().numpy()})[0]
-        return OnnxImage(output)
+        output = self.session.run([output_name], {
+            input_name: image.cpu().numpy()
+        })[0]
+        return OnnxTensor(output)
 
     def eval(self) -> None:
         pass