import  matplotlib.pyplot as plt

fig = plt.gcf()

fig.canvas.manager.set_window_title('窗口标题')

import onnx
from onnxconverter_common import float16
model = onnx.load("fp32_model.onnx")
model_fp16 = float16.convert_float_to_float16(model, keep_io_types=True)

onnx.save(model_fp16, "fp16_model.onnx")

一、安装必要的软件

    1、 pip3  install   symforce

    2、 pip3  install   notebook==6.5.6

二、运行Jupyter NoteBook

   在Linux终端下执行:

    jupyter-notebook

    执行该命令后，会自动调起浏览器:

三、新建Python3(IPython)

四、输入Python代码并执行

import symforce
symforce.set_symbolic_api("symengine")
from symforce.notebook_util import display
import symforce.symbolic as sf


x = sf.Symbol("x")
y = sf.Symbol("y")
expr = x**2 + sf.sin(y) / x**2
display(expr)

import cv2
import os
import sys

# Function to extract frames from a video until reaching the desired frame count
def extract_frames(video_file):
    cap = cv2.VideoCapture(video_file)

    frame_rate = 2  # Desired frame rate (1 frame every 0.5 seconds)
    frame_count = 0

    # Get the video file's name without extension
    video_name = os.path.splitext(os.path.basename(video_file))[0]

    # Create an output folder with a name corresponding to the video
    output_directory = f"{video_name}_frames"
    os.makedirs(output_directory, exist_ok=True)

    while True:
        ret, frame = cap.read()

        if not ret:
            break

        frame_count += 1

        # Only extract frames at the desired frame rate
        if frame_count % int(cap.get(5) / frame_rate) == 0:
            output_file = f"{output_directory}/frame_{frame_count}.png"
            cv2.imwrite(output_file, frame)
            print(f"Frame {frame_count} has been extracted and saved as {output_file}")
        if frame_count >= 30:
            break

    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    if len(sys.argv)<2:
        print("Usage:\n  < mp4 file name >")
        sys.exit()
    if 2== len(sys.argv):
        files = sys.argv[1:]
        video_file = files[0]
        sys.exit(extract_frames(video_file))
    else:

        sys.exit()

1、MindStudio 安装

2、Python3环境安装

    MindStudio只支持Python3.7.5，因此需要按照文档《驱动和开发环境安装指南》中的内容安装python.

    由于操作系统自带的Python版本不一定是3.7.5，因此每次执行: MindStudio.sh前，需要声明Python环境变量:

    export LD_LIBRARY_PATH=/usr/local/python3.7.5/lib:$LD_LIBRARY_PATH
    export PATH=/usr/local/python3.7.5/bin:$PATH

    当然，为了方便，也可以直接把上述两行代码写入MindStudio.sh的最前面，如下图所示: