rhee-elten

from contextlib import contextmanager
from collections.abc import Iterable
import matplotlib.pyplot as plt
import cv2
import numpy as np


@contextmanager
def fourplots(cols=4, figsize=(11, 2.5), dpi=100, set_axis=False, grid_props=None, **kwargs):
    

rhee-elten

import numpy as np
from tqdm.auto import tqdm


def make_circle_kernel(radius):
    """

    test:
    
    for radius in [5]:

rhee-elten

"""
HOUGH_GRADIENT_ALT (Scharr algorithm) 의 경우
파라메터 권장값이 소개되어 있어서 이를 적용해 본다.

"""

from functools import partial
from time import perf_counter

import cv2

rhee-elten

# obj_summary.py
# gist: https://gist.github.com/rhee-elten/84569d1a5ef3bfee37beac52c4d7ac04
import sys
from functools import partial

import numpy as np
import pandas as pd


def obj_summary(obj, *, key=None, prefix="", visited=None):

rhee-elten

#!/usr/bin/env python
# coding: utf-8

# In[1]:


## gist: https://gist.github.com/rhee-elten/ca633edcf039069015e8ccd7faaa099a
## keras 모델로 p1 데이터셋을 학습하고, 테스트 데이터셋에 대한 gradcam 을 추출
## 93.87% 94.86% VAL AUC 최고치 였던 저장 파일 사용
_backbone = 'DenseNet169'

rhee-elten

###########################################
# video streaming using gst or vc.txt
# gist: https://gist.github.com/rhee-elten/566be98345a95cad67f053f565462333
###########################################

[gst]

# run-gst-8080-http.bash
set -x
gst-launch-1.0 v4l2src ! \

rhee-elten

#!/usr/bin/env python
# coding: utf-8
## cuda_select_best_memfree.py 는 python2 에서도 실행되면 좋겠다. (시스템 파이썬 사용)
## gist https://gist.github.com/rhee-elten/223124ba106e7b9927078a4a1a8c320e
from __future__ import print_function
import sys
import os
import subprocess

rhee-elten

:
if ! -z "$DEVPI_FORWARD"
then
  docker run -dit --restart unless-stopped \
    -p 3141:3141 \
    --name devpi alpine/socat:1.7.4.4 \
    tcp-listen:3141,fork,reuseaddr tcp-connect:$DEVPI_FORWARD:3141
else
  docker run -dit --restart unless-stopped \
    -p 3141:3141 \

rhee-elten

:
<<EEE >/dev/null

https://github.com/EpicWink/proxpi

Environment variables

PROXPI_INDEX_URL: index URL, default: https://pypi.org/simple/
PROXPI_INDEX_TTL: index cache time-to-live in seconds, default: 30 minutes. Disable index-cache by setting this to 0
PROXPI_EXTRA_INDEX_URLS: extra index URLs (comma-separated)

rhee-elten

"""
fasterrcnn 에서 동작하도록 하기 위해서는 keras_cv 에 다음 패치 필요:

keras_cv/layers/object_detection/anchor_generator.py

line 258:

        stride = self.stride
        # make sure range of `cx` is within limit of `image_width` with
        # `stride`, also for sizes where `image_width % stride != 0`.