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# Line 29

from widerface_val import bbox_vote 
from warnings import filterwarnings # <----------

filterwarnings("ignore") # <----------

plt.switch_backend('agg')

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{
	"NotebookApp": {
        "open_browser": false,
        "port": 8887,
        "ip": "0.0.0.0",
	"allow_origin": "*",
        "notebook_dir": "c:\\users\\admin\\",
        "certfile": "c:\\users\\admin\\.jupyter\\mycert.pem",
        "keyfile": "c:\\users\\admin\\.jupyter\\mykey.key",
        "allow_remote_access": true,

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cmake -D CMAKE_BUILD_TYPE=RELEASE \
    -D CMAKE_INSTALL_PREFIX=/usr/local \
    -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \
    -D PYTHON3_LIBRARY=`python -c 'import subprocess ; import sys ; s = subprocess.check_output("python-config --configdir", shell=True).decode("utf-8").strip() ; (M, m) = sys.version_info[:2] ; print("{}/libpython{}.{}.dylib".format(s, M, m))'` \
    -D PYTHON3_INCLUDE_DIR=`python -c 'import distutils.sysconfig as s; print(s.get_python_inc())'` \
    -D PYTHON3_EXECUTABLE=$VIRTUAL_ENV/bin/python \
    -D BUILD_opencv_python2=OFF \
    -D BUILD_opencv_python3=ON \
    -D INSTALL_PYTHON_EXAMPLES=ON \
    -D INSTALL_C_EXAMPLES=OFF \

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{
	"NotebookApp": {
        "open_browser": false,
        "port": 8888,
        "ip": "0.0.0.0",
	"allow_origin": "*",
        "notebook_dir": "/mnt/c/users/admin/",
        "certfile": "/home/user/.jupyter/mycert.pem",
        "keyfile": "/home/user/.jupyter/mykey.key",
        "allow_remote_access": true,

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parser = argparse.ArgumentParser(description='DSFD:Dual Shot Face Detector')

parser.add_argument('--trained_model', default='weights/WIDERFace_DSFD_RES152.pth',
                    type=str, help='Trained state_dict file path to open')
parser.add_argument('--save_folder', default='eval_tools/', type=str,
                    help='Dir to save results')
parser.add_argument('--visual_threshold', default=0.1, type=float,
                    help='Final confidence threshold')
parser.add_argument('--cuda', default=False, type=bool,
                    help='Use cuda to train model')

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from fastai.vision.all import *
from fastbook import *

file_directory = untar_data(URLs.MNIST_SAMPLE)

training_3_file_paths = (file_directory/'train'/'3').ls().sorted()
training_3_tensors = [tensor(Image.open(file_path)) for file_path in training_3_file_paths]
training_3_tensors = torch.stack(training_3_tensors).float() / 255
training_7_file_paths = (file_directory/'train'/'7').ls().sorted()
training_7_tensors = [tensor(Image.open(file_path)) for file_path in training_7_file_paths]

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---

REFERENCES FOR LEARNING & USING APPLESCRIPT Modified: 2018/06/19 18:47

---

NOTES

AppleScript is a rather peculiar scripting language to learn.

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# sets user to default user for web server
user www-data;

# sets number of cpu cores to use
worker_processes auto;

# customizes how to handle connections
events {
    
    # sets number of connections to use per cpu core

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// Transform > Position > Code


var text_composition = comp("Top");
var text_layer = text_composition.layer("Subtitle");
var text_rectangle = text_layer.sourceRectAtTime();
var text_left = text_rectangle.left;
var text_top = text_rectangle.top;
var text_width = text_rectangle.width;
var text_height = text_rectangle.height;