HI i have several questions about input size
i have trained darknet yolov3 with input size 192x96
1. when i dumped tensorflow model using tensorflow-yolo-v3, it made error because of input size.
so i changed anchors in yolo_v3.py and input size in convert_weight.py & convert_weight_pb.py
also i changed _upsample()function in yolo_v3.py like below
new_height = out_shape
new_width = out_shape
#new_height = out_shape
#new_width = out_shape
so i got ckpt file and pb file
2. and i run mo_tf.py with option --input_shape [1, 96,192,3]
so i got bin,mapping, xml files
3. Lastly, i am trying to inference my model using object_detection_demo_yolov3_async.py
but it gives me a message that height and weight should be equal
Is there anyway i can use my own input size? not square shape input size
Thanks for reaching out, the demo only supports square inputs. I have not tried using a non-squared input with YOLOv3 and the OpenVINO toolkit. You may have to modify the demo to meet your needs. However, I am uncertain if this will work. Is there a particular reason why you need to keep the input shape to 192 x 96?