1

app/service/super_resolution/test.py

@@ -0,0 +1,28 @@
+import time
+
+import cv2
+import numpy as np
+import torch
+import tritonclient.http as httpclient
+from PIL import Image
+
+triton_client = httpclient.InferenceServerClient(url=f"10.1.1.150:7000")
+
+sample = cv2.imread("comic2.png", cv2.IMREAD_COLOR).astype(np.float32) / 255.
+sample = np.transpose(sample if sample.shape[2] == 1 else sample[:, :, [2, 1, 0]], (2, 0, 1))
+sample = torch.from_numpy(sample).float().unsqueeze(0).numpy()
+inputs = [
+    httpclient.InferInput("input", sample.shape, datatype="FP32")
+]
+inputs[0].set_data_from_numpy(sample, binary_data=True)
+start_time = time.time()
+results = triton_client.infer(model_name="super_resolution", inputs=inputs)
+print(time.time() - start_time)
+sr_output = torch.from_numpy(results.as_numpy(f"output"))
+output = sr_output.data.squeeze().float().cpu().clamp_(0, 1).numpy()
+if output.ndim == 3:
+    output = np.transpose(output[[2, 1, 0], :, :], (1, 2, 0))  # CHW-RGB to HCW-BGR
+output = (output * 255.0).round().astype(np.uint8)
+# cv2.imshow("", output)
+# cv2.waitKey(0)
+cv2.imwrite("comic3.png", output)