Yolov5-Lite with shuffle block convert to tflie

[ppogg]

Unbelievable, this warehouse is really great！！！

[PINTO0309]

I will not respond unless you provide ONNX or OpenVINO IR. I really dislike sloppy issues.

77 "Yolov5 with Shuffle_Block model conversion error, ValueError: Dimension size must be evenly divisible by 3 but is 16"

[ppogg]

sorry sir，like this： v5lite-s.xml: https://drive.google.com/file/d/1POkWJaGG8qyebf1PCVWp_fMTmFJ4jl1C/view?usp=sharing v5lte-s.bin: https://drive.google.com/file/d/1Mq8cFc2rTX1KwFeaSc3bUlVyga1bWl5H/view?usp=sharing The dataset is coco

[PINTO0309]

There seems to be no post-processing at all, are you sure this is the complete model? This is not a problem at all for conversion, but I just felt that post-processing would be better if the model is to be used for end-to-end.

[PINTO0309]

Can be converted normally.

xhost +local: && \
docker run --gpus all -it --rm \
-v `pwd`:/home/user/workdir \
-v /tmp/.X11-unix/:/tmp/.X11-unix:rw \
--device /dev/video0:/dev/video0:mwr \
--net=host \
-e XDG_RUNTIME_DIR=$XDG_RUNTIME_DIR \
-e DISPLAY=$DISPLAY \
--privileged \
ghcr.io/pinto0309/openvino2tensorflow:latest

H=640
W=640
MODEL=v5lite_s
openvino2tensorflow \
--model_path saved_model/openvino/FP32/${MODEL}_${H}x${W}.xml \
--output_saved_model \
--output_pb \
--output_no_quant_float32_tflite

• v5lite-s.tflite

[ppogg]

My God, can you provide a converted model? I want to see the difference with my tflite after converting.

[PINTO0309]

saved_model.zip

[ppogg]

Thankyou sir. By the way, I watched this warehouse for a long time last night. It was really practical.

[PINTO0309]

Thank you. If models with post-processing are provided, I will convert them all and share them with my model zoo. https://github.com/PINTO0309/PINTO_model_zoo

[ppogg]

Of course sir, this is my honor，like this： This IR model includes post-processing： https://drive.google.com/file/d/1zvhzWmS_8tQEJPRLWlSbehXT_wRVY45P/view?usp=sharing

[ppogg]

By the way, the model you just converted for me does not work, but someone used this repo to convert yolov5 before and work: https://github.com/lp6m/yolov5s_android/tree/master/convert_model. you converted for me: before: I use the same detect.py. May be is a new problem, thankyou sir~

[PINTO0309]

• OpenVINO to TensorFlow to ONNX and TFLite, Comparison of inference results.

import onnxruntime
import tensorflow as tf
import time
import numpy as np
from pprint import pprint

H=640
W=640
MODEL='model_float32'

############################################################

onnx_session = onnxruntime.InferenceSession(f'saved_model_{H}x{W}/model_float32.onnx')
input_name = onnx_session.get_inputs()[0].name
output_name = onnx_session.get_outputs()[0].name

roop = 1
e = 0.0
result = None
inp = np.ones((1,3,H,W), dtype=np.float32)
for _ in range(roop):
    s = time.time()
    result = onnx_session.run(
        [output_name],
        {input_name: inp}
    )
    e += (time.time() - s)
print('ONNX output @@@@@@@@@@@@@@@@@@@@@@@
print(f'elapsed time: {e/roop*1000}ms')
print(f'shape: {result[0].shape}')
pprint(result)

############################################################

interpreter = tf.lite.Interpreter(model_path=f'saved_model_{H}x{W}/model_float32.tflite', num_threads=4)
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()

roop = 1
e = 0.0
result = None
inp = np.ones((1,H,W,3), dtype=np.float32)
for _ in range(roop):
    s = time.time()
    interpreter.set_tensor(input_details[0]['index'], inp)
    interpreter.invoke()
    result = interpreter.get_tensor(output_details[0]['index'])
    e += (time.time() - s)
print('tflite output @@@@@@@@@@@@@@@@@@@@@@@
print(f'elapsed time: {e/roop*1000}ms')
print(f'shape: {result.shape}')
pprint(result)

user@ubuntu2004:~/workdir$ python3 onnx_tflite_test.py 
ONNX output @@@@@@@@@@@@@@@@@@@@@@@
elapsed time: 29.294729232788086ms
shape: (1, 25200, 85)
[array([[[2.51785994e+00, 2.60093212e+00, 1.49863968e+01, ...,
         4.47389483e-03, 1.61233544e-03, 1.08805299e-02],
        [1.17213287e+01, 3.59181929e+00, 2.65871239e+01, ...,
         3.91250849e-03, 1.57558918e-03, 1.05172098e-02],
        [1.90585785e+01, 3.66961241e+00, 3.22659492e+01, ...,
         3.77982855e-03, 1.24087930e-03, 1.00672245e-02],
        ...,
        [5.61473145e+02, 6.06712646e+02, 1.61073944e+02, ...,
         7.55631924e-03, 7.73429871e-04, 1.77630782e-03],
        [5.85584778e+02, 6.07984070e+02, 1.28446884e+02, ...,
         7.52204657e-03, 8.94069672e-04, 2.54270434e-03],
        [6.17867249e+02, 6.16864014e+02, 1.56085968e+02, ...,
         7.01209903e-03, 9.43809748e-04, 2.71356106e-03]]], dtype=float32)]

INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
tflite output @@@@@@@@@@@@@@@@@@@@@@@
elapsed time: 54.502010345458984ms
shape: (1, 25200, 85)
array([[[2.5178699e+00, 2.6009421e+00, 1.4986400e+01, ...,
         4.4739130e-03, 1.6123326e-03, 1.0880618e-02],
        [1.1721323e+01, 3.5918303e+00, 2.6587116e+01, ...,
         3.9125220e-03, 1.5755324e-03, 1.0517325e-02],
        [1.9058573e+01, 3.6696162e+00, 3.2265942e+01, ...,
         3.7798532e-03, 1.2408829e-03, 1.0067256e-02],
        ...,
        [5.6147308e+02, 6.0671265e+02, 1.6107385e+02, ...,
         7.5563113e-03, 7.7344757e-04, 1.7763070e-03],
        [5.8558478e+02, 6.0798407e+02, 1.2844681e+02, ...,
         7.5220633e-03, 8.9407619e-04, 2.5427316e-03],
        [6.1786725e+02, 6.1686395e+02, 1.5608585e+02, ...,
         7.0121274e-03, 9.4381260e-04, 2.7135969e-03]]], dtype=float32)

[ppogg]

Oh, I know. May be something I get wrong. Thankyou very much！

[PINTO0309]

Commited.

• TFLite Float32, Float16, INT8, Dynamic range quantization, ONNX, TFJS, TensorRT, OpenVINO IR FP32/FP16, Myriad Inference Engin Blob, CoreML https://github.com/PINTO0309/PINTO_model_zoo/tree/main/180_YOLOv5-Lite

The input resolution is too large, so I aborted the conversion to EdgeTPU.

[ppogg]

I like it, good jobs sir!

[PINTO0309]

Since there seems to be no particular progress, I will close it once. This is to list the tasks that I will need to do in the future. Please post another issue when you need it.

[Houangnt]

sorry sir，like this： v5lite-s.xml: https://drive.google.com/file/d/1POkWJaGG8qyebf1PCVWp_fMTmFJ4jl1C/view?usp=sharing v5lte-s.bin: https://drive.google.com/file/d/1Mq8cFc2rTX1KwFeaSc3bUlVyga1bWl5H/view?usp=sharing The dataset is coco

How to get v5lite.xml from my model ?. I try to put your v5lite-lite.xml and my v5lite-lite.bin and got this error : After that, i put 2 your file xml and bin, i dont get any error. I'm wondering if I have to use my own v5-lite.xml and v5-lite.bin file to convert them but i dont know how to get v5lite.xml.

[PINTO0309]

Please ask the author himself. https://github.com/ppogg/YOLOv5-Lite