Hello,
I am trying to work on image classification python script that takes my own pre trained alexnet model and try to classify images.
I am trying first on Windows10 but the end goal is to make it work on a OpenVino Starter Platform.
The script works pretty well. But if I tried to make it executable and run it, it gives some errors.
The script is as follows:
import sys
import time
from pathlib import Path
import cv2
import matplotlib.pyplot as plt
#import mo_onnx
import numpy as np
import torch
from openvino.inference_engine import IECore
import argparse
import os
import openvino.inference_engine.constants
parser = argparse.ArgumentParser()
parser.add_argument("-m")
parser.add_argument("-i")
args = parser.parse_args()
model=os.path.abspath(args.m)
imageName=os.path.abspath(args.i)
BASE_MODEL_NAME = model
model_path = Path(BASE_MODEL_NAME).with_suffix(".pytorch")
onnx_path = model_path.with_suffix(".onnx")
ir_path = model_path.with_suffix(".xml")
model = torch.load(model_path).cpu().eval()
if not onnx_path.exists():
dummy_input = torch.randn(1, 3, 224, 224)
# For the Fastseg model, setting do_constant_folding to False is required
# for PyTorch>1.5.1
torch.onnx.export(
model,
dummy_input,
onnx_path,
opset_version=11,
do_constant_folding=False,
)
print(f"ONNX model exported to {onnx_path}.")
else:
print(f"ONNX model {onnx_path} already exists.")
#mo_path = str(Path(mo_onnx.__file__))
# Construct the command for Model Optimizer
#mo_command = f""""{sys.executable}"
# "{mo_path}"
# --input_model "{onnx_path}"
# --input_shape "[1,3, 224, 224]"
# --mean_values "[0.485, 0.456, 0.406]"
# --scale_values "[58.395, 57.12 , 57.375]"
# --data_type "FP16"
# --output_dir "{model_path.parent}"
# """
#print(model_path.parent)
#mo_command = " ".join(mo_command.split())
print("Model Optimizer command to convert the ONNX model to OpenVINO:")
#print(mo_command)
if not ir_path.exists():
print("Exporting ONNX model to IR... This may take a few minutes.")
# os.system(mo_command)
else:
print(f"IR model {ir_path} already exists.")
def normalize(image: np.ndarray) -> np.ndarray:
"""
Normalize the image to the given mean and standard deviation
for CityScapes models.
"""
image = image.astype(np.float32)
mean = (0.485, 0.456, 0.406)
std = (0.229, 0.224, 0.225)
image /= 255.0
image -= mean
image /= std
return image
ie = IECore()
net_onnx = ie.read_network(model=onnx_path)
exec_net_onnx = ie.load_network(network=net_onnx, device_name="CPU")
input_layer_onnx = next(iter(exec_net_onnx.input_info))
output_layer_onnx = next(iter(exec_net_onnx.outputs))
# Run the Inference on the Input image...
res_onnx = exec_net_onnx.infer(
inputs={input_layer_onnx: normalized_input_image}
)
res_onnx = res_onnx[output_layer_onnx]
result_mask_onnx = np.squeeze(np.argmax(res_onnx, axis=1)).astype(np.uint8)
if (result_mask_onnx == 0):
print("Your image is not an RPW")
elif (result_mask_onnx == 1):
print("Your image is RPW")
I turn it into executable using the following commands;
>> <path>\openvino_2021\bin\setupvars.bat
>> pyinstaller --onefile --add-data "<path>\openvino_2021\deployment_tools\inference_engine\bin\intel64\Release\plugins.xml;." --paths "<path>\openvino_2021\python\python3\cv2" script.py
The error is as follows:
[14976] WARNING: file already exists but should not: <path>\Temp\_MEI149762\torch\_C.cp38-win_amd64.pyd Traceback (most recent call last): File "script.py", line 5, in <module> import cv2 File "PyInstaller\loader\pyimod03_importers.py", line 546, in exec_module File "cv2\__init__.py", line 129, in <module> File "cv2\__init__.py", line 72, in bootstrap File "cv2\__init__.py", line 70, in load_first_config ImportError: OpenCV loader: missing configuration file: ['config.py']. Check OpenCV installation.
[33260] Failed to execute script 'script' due to unhandled exception!
Can you please help with this error and if you have a way to make this script working after that on linux machine that will have the FPGA connected to it?
