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Add args to original Yolo script to be able to run it standalone #663

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Add args to original Yolo script to be able to run it standalone #663

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99a0682
Add args to original Yolo script to be able to run it standalone
natke Feb 17, 2024
11fabbe
Update tutorials/yolo_e2e.py
natke Feb 27, 2024
c84de45
Add script dir
natke Feb 17, 2024
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26 changes: 21 additions & 5 deletions tutorials/yolo_e2e.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,8 @@
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import argparse
import numpy
import os

from pathlib import Path
import onnxruntime_extensions
Expand Down Expand Up @@ -34,30 +36,44 @@ def add_pre_post_processing_to_yolo(input_model_file: Path, output_model_file: P
add_ppp.yolo_detection(input_model_file, output_model_file, "jpg", onnx_opset=18)


def run_inference(onnx_model_file: Path):
def run_inference(onnx_model_file: Path, test_image: Path):
import onnxruntime as ort
import numpy as np

providers = ['CPUExecutionProvider']
session_options = ort.SessionOptions()
session_options.register_custom_ops_library(onnxruntime_extensions.get_library_path())

image = np.frombuffer(open('../test/data/ppp_vision/wolves.jpg', 'rb').read(), dtype=np.uint8)
image = np.frombuffer(open(f'{test_image}', 'rb').read(), dtype=np.uint8)
session = ort.InferenceSession(str(onnx_model_file), providers=providers, sess_options=session_options)

inname = [i.name for i in session.get_inputs()]
inp = {inname[0]: image}
output = session.run(['image_out'], inp)[0]
output_filename = '../test/data/result.jpg'
filename, extension = os.path.splitext(test_image)
output_filename = Path(f'{filename}.out{extension}')
open(output_filename, 'wb').write(output)
from PIL import Image
Image.open(output_filename).show()


if __name__ == '__main__':

script_dir = Path( __file__ ).parent.absolute()

# YOLO version. Tested with 5 and 8.
version = 8
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onnx_model_name = Path(f"../test/data/yolov{version}n.onnx")

parser = argparse.ArgumentParser("Add pre and post processing to the YOLOv8 model.")
parser.add_argument("--onnx_model_path", type=Path, default=f"yolov{version}n.onnx",
help="The location and name of the file to output the ONNX YOLO model.")
parser.add_argument("--test_image", type=Path, default=f"{script_dir}/data/wolves.jpg")

args = parser.parse_args()
onnx_model_path = args.onnx_model_path


onnx_model_name = Path(f"{onnx_model_path}")
if not onnx_model_name.exists():
print("Fetching original model...")
get_yolo_model(version, str(onnx_model_name))
Expand All @@ -66,4 +82,4 @@ def run_inference(onnx_model_file: Path):
print("Adding pre/post processing...")
add_pre_post_processing_to_yolo(onnx_model_name, onnx_e2e_model_name)
print("Testing updated model...")
run_inference(onnx_e2e_model_name)
run_inference(onnx_e2e_model_name, args.test_image)
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