supermachine-tobacco/01_dataset.ipynb
2022-07-18 16:33:55 +08:00

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{
"cells": [
{
"cell_type": "markdown",
"source": [
"# 彩色图像读取与分析"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
}
},
{
"cell_type": "code",
"execution_count": 1,
"outputs": [],
"source": [
"import cv2\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"%matplotlib inline"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "markdown",
"source": [
"## 单张图片分析"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
}
},
{
"cell_type": "code",
"execution_count": 2,
"outputs": [],
"source": [
"img_path = r\"data/dataset/img/beijing.bmp\"\n",
"label_path = r\"data/dataset/label/beijing.bmp\""
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "code",
"execution_count": 3,
"outputs": [],
"source": [
"# 读取图片和色彩空间转换\n",
"img = cv2.imread(img_path)\n",
"label_img = cv2.imread(label_path)\n",
"img = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)\n",
"# 从opencv的色彩空间到Photoshop的色彩空间\n",
"alpha, beta = np.array([100 / 255, 1, 1], dtype=float), np.array([0, -128, -128], dtype=float)\n",
"img = img * alpha + beta\n",
"img = np.asarray(np.round(img, 0), dtype=int)"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "code",
"execution_count": 4,
"outputs": [],
"source": [
"# 构建数据集\n",
"color_dict = {(0, 0, 255): 'tobacco', (255, 0, 0): 'background'}\n",
"dataset = {label: img[np.all(label_img == color, axis=2)] for color, label in color_dict.items()}"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "code",
"execution_count": 5,
"outputs": [
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# 观察色彩分布情况\n",
"fig, axs = plt.subplots()\n",
"for label, data in dataset.items():\n",
" l, a, b = [data[:, i] for i in range(3)]\n",
" axs.scatter(a, b, label=label, alpha=0.1)\n",
"axs.set_xlim(-127, 127)\n",
"axs.set_ylim(-127, 127)\n",
"axs.set_xlabel('a')\n",
"axs.set_ylabel('b')\n",
"plt.legend()\n",
"plt.show()"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "markdown",
"source": [
"单张图片仅能够观察到单一类别的色彩分布情况, 但已经可以看出背景的颜色分布情况多集中在较为暗的区域"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
}
},
{
"cell_type": "markdown",
"source": [
"## 多张图片分析\n",
"为了能够有效分析各类杂质的色彩分布情况, 构建多个类别的读取函数与图形绘制函数"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
}
},
{
"cell_type": "code",
"execution_count": 6,
"outputs": [],
"source": [
"from utils import read_labeled_img,lab_scatter"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "code",
"execution_count": 7,
"outputs": [],
"source": [
"dataset = read_labeled_img(\"data/dataset\", color_dict={(0, 0, 255): \"yangeng\", (255, 0, 0): \"bejing\", (0, 255, 0): \"hongdianxian\", (255, 0, 255): \"chengsebangbangtang\",(0, 255, 255): \"lvdianxian\"})"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "code",
"execution_count": 8,
"outputs": [
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"lab_scatter(dataset, class_max_num=200, is_3d=True)"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "markdown",
"source": [
"上图所示是LAB色彩空间内的分布情况,每个类别只取了200个样本这样子看来各个物体的颜色重叠是不太严重的"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
}
},
{
"cell_type": "code",
"execution_count": 10,
"outputs": [
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"lab_scatter(dataset, class_max_num=10000, is_3d=True)"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "markdown",
"source": [
"但是如果用很多样本来看,情况就不容乐观了,重叠还是很严重的,尤其是和背景以及橙色棒棒糖之间重叠特别厉害"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
}
},
{
"cell_type": "code",
"execution_count": 11,
"outputs": [
{
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"lab_scatter(dataset, is_3d=False)"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "markdown",
"source": [
"如果我们抛弃亮度通道,只看颜色,就像上图这样,从这个角度看,烟梗的颜色和其他颜色之间的重叠度超级高呢。所以必须同时考虑亮度和其他类型的颜色。"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%% md\n"
}
}
},
{
"cell_type": "code",
"execution_count": 9,
"outputs": [],
"source": [],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 0
}