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@@ -37,3 +37,22 @@ depth_anything_v2_vits_ax620e.axmodel filter=lfs diff=lfs merge=lfs -text
 depth_anything_v2_vits_ax650.axmodel filter=lfs diff=lfs merge=lfs -text
 python/examples/demo19.jpg filter=lfs diff=lfs merge=lfs -text
 python/output.png filter=lfs diff=lfs merge=lfs -text
+python/examples/demo01.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo02.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo03.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo04.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo05.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo06.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo07.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo08.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo09.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo10.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo11.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo12.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo13.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo14.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo15.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo16.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo17.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo18.jpg filter=lfs diff=lfs merge=lfs -text
+python/examples/demo20.jpg filter=lfs diff=lfs merge=lfs -text

python/python/infer.py

@@ -0,0 +1,50 @@
+import argparse
+import cv2
+import numpy as np
+import axengine as axe
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--img",
+        type=str,
+        required=True,
+        help="Path to input image.",
+    )
+    parser.add_argument(
+        "--model",
+        type=str,
+        required=True,
+        help="Path to axmodel model.",
+    )
+    
+    return parser.parse_args()
+
+
+def infer(img: str, model: str, viz: bool = False):
+    img_raw = cv2.imread(img)
+    image = cv2.cvtColor(img_raw, cv2.COLOR_BGR2RGB) 
+    orig_h, orig_w = image.shape[:2]
+    image = cv2.resize(image, (518,518))
+    image = image[None]
+
+    session = axe.InferenceSession(model)
+    
+    depth = session.run(None, {"input": image})[0]
+
+    depth = cv2.resize(depth[0, 0], (orig_w, orig_h))
+    depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255.0
+    depth = depth.astype(np.uint8)
+
+    depth_color = cv2.applyColorMap(depth, cv2.COLORMAP_INFERNO)
+
+    combined_result = cv2.hconcat([img_raw,  depth_color])
+            
+    cv2.imwrite("output-ax.png", combined_result)
+    
+    return depth
+
+
+if __name__ == "__main__":
+    args = parse_args()
+    infer(**vars(args))

python/python/infer_onnx.py

@@ -0,0 +1,56 @@
+import argparse
+import cv2
+import numpy as np
+import onnxruntime as ort
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--img",
+        type=str,
+        required=True,
+        help="Path to input image.",
+    )
+    parser.add_argument(
+        "--model",
+        type=str,
+        required=True,
+        help="Path to ONNX model.",
+    )
+    
+    return parser.parse_args()
+
+
+def infer(img: str, model: str, viz: bool = False):
+    img_raw = cv2.imread(img)
+    image = cv2.cvtColor(img_raw, cv2.COLOR_BGR2RGB) 
+    orig_h, orig_w = image.shape[:2]
+    image = cv2.resize(image, (518,518) )
+    mean = np.array([123.675, 116.28, 103.53],dtype=np.float32).reshape(1,1,3)
+    std = np.array([58.395, 57.12, 57.375],dtype=np.float32).reshape(1,1,3)
+
+    image = (image-mean)/std 
+    image = image.transpose(2,0,1)
+    image = image[None]
+
+    session = ort.InferenceSession(
+        model, providers=["CUDAExecutionProvider", "CPUExecutionProvider"]
+    )
+    depth = session.run(None, {"input": image})[0]
+
+    depth = cv2.resize(depth[0, 0], (orig_w, orig_h))
+    depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255.0
+    depth = depth.astype(np.uint8)
+
+    depth_color = cv2.applyColorMap(depth, cv2.COLORMAP_INFERNO)
+
+    combined_result = cv2.hconcat([img_raw,  depth_color])
+            
+    cv2.imwrite("output-onnx.png", combined_result)
+    
+    return depth
+
+
+if __name__ == "__main__":
+    args = parse_args()
+    infer(**vars(args))

python/python/requirements.txt

@@ -0,0 +1,3 @@
+onnx
+onnxruntime
+opencv-python