How to resizing Input format for YOLOv5s with Hailo Parser

General
1

Hi Hailo

Currently, I want to run an I420 input image(540, 640) to yolov5s model(640, 640).

The image flow I’m considering is..
image[540, 640] → i420 to hailo yuv → yuv to rgb → resize [640, 640] → yolov5s model.

However, to change the input image format, it seems impossible to set the input shape to (540, 640) using the hailo parser onnx --tensor-shapes

Additionally, modifying net_input_shapes the method provided in the Hailo tutorial doesn’t seem to work either.

And here is the model script that I used

model_script_commands = [
‘normalization1 = normalization([0.0, 0.0, 0.0], [255.0, 255.0, 255.0])\n’
‘change_output_activation(sigmoid)\n’
‘resize_input1 = resize(resize_shapes=[640,640])\n’
‘yuv_to_rgb1 = input_conversion(yuv_to_rgb)\n’
‘format_conversion = input_conversion(input_layer1, i420_to_hailo_yuv, emulator_support = False)\n’
‘nms_postprocess(“./yolov5s_personface.json”, yolov5, engine=cpu)\n’
‘post_quantization_optimization(finetune, policy=enabled, learning_rate=0.0001, epochs=4, dataset_size=10, loss_factors=[1.0, 1.0, 1.0], loss_types=[l2rel, l2rel, l2rel], loss_layer_names=[conv70, conv63, conv55])\n’
]

image
image289×860 26.8 KB

Thanks

2

Hi @roiyim
The model is configured to accept (640,640) input. Can you please elaborate why you need to change onnx input shape to (540,640)?

3

Hi shashi

The input image size used in our application is 540 x 640.
Currently, we are resizing the images on the host before inputting them into the Hailo8, but the performance is not good.
Due to the high cost of other applications running on the host, we intend to reduce host computation.
We hope to utilize the resize feature within the Hailo8, as mentioned in the DFC document.
If it is possible to input 540 x 640 images into the Hailo8 and transform them to 640 x 640 using the resize function, I would like to know the method to do so.

Thanks