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dip_canny_edge_detection.ipynb
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{ | |
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\n" | |
}, | |
"metadata": {} | |
}, | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"ok!\n" | |
] | |
} | |
] | |
} | |
}, | |
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} | |
}, | |
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}, | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "view-in-github", | |
"colab_type": "text" | |
}, | |
"source": [ | |
"<a href=\"https://colab.research.google.com/gist/dsaint31x/2afa8252d9134452db87ee5046ba1d3a/dip_canny_edge_detection.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"source": [ | |
"# Canny Edge Detection" | |
], | |
"metadata": { | |
"id": "zZYfY7d25Odu" | |
} | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"id": "GGmlCGlPzuGg" | |
}, | |
"outputs": [], | |
"source": [ | |
"import cv2\n", | |
"import numpy as np\n", | |
"import matplotlib.pyplot as plt\n", | |
"import requests\n", | |
"from google.colab.patches import cv2_imshow # for goole colab" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"def get_img_cv(url):\n", | |
" image_ndarray = np.asarray(bytearray(requests.get(url).content), dtype=np.uint8)\n", | |
" img = cv2.imdecode(image_ndarray, cv2.IMREAD_COLOR)\n", | |
" print(img.shape)\n", | |
" return img" | |
], | |
"metadata": { | |
"id": "Dkh_NnKzzuwe" | |
}, | |
"execution_count": null, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"url = 'https://raw.githubusercontent.com/dsaint31x/OpenCV_Python_Tutorial/master/images/sudoku.jpg'\n", | |
"\n", | |
"#img = cv2.imread(img_path)\n", | |
"img = get_img_cv(url)\n", | |
"print(img.shape,img.max(),img.min())" | |
], | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/" | |
}, | |
"id": "Y7mRP3bIzwDc", | |
"outputId": "ab9c626f-c4f1-48cf-af33-0913100990a2" | |
}, | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"(320, 317, 3)\n", | |
"(320, 317, 3) 226 0\n" | |
] | |
} | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"edge = cv2.Canny(img,120,200)\n", | |
"print(edge.shape)\n", | |
"cv2_imshow(edge)" | |
], | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 356 | |
}, | |
"id": "ymr2NfyHz1DE", | |
"outputId": "6570fc69-b56d-4c30-8b9b-6106a0c9895d" | |
}, | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"(320, 317)\n" | |
] | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"text/plain": [ | |
"<PIL.Image.Image image mode=L size=317x320 at 0x7EFCEA113280>" | |
], | |
"image/png": 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\n" | |
}, | |
"metadata": {} | |
} | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"source": [ | |
"# For ipynb file" | |
], | |
"metadata": { | |
"id": "b7xmkFgw5T1L" | |
} | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"from __future__ import print_function\n", | |
"from ipywidgets import interact, interactive, fixed, interact_manual,IntSlider\n", | |
"import ipywidgets as widgets\n", | |
"\n", | |
"from IPython.display import clear_output" | |
], | |
"metadata": { | |
"id": "ubIxhGUMz1nU" | |
}, | |
"execution_count": null, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"min_slide = IntSlider(min=0, max=255, step=1, value=90)\n", | |
"max_slide = IntSlider(min=0, max=255, step=1, value=100)\n", | |
"\n", | |
"def f(min,max):\n", | |
" clear_output(wait=True)\n", | |
" if max < min:\n", | |
" print(f'inavailable arguments : min={min}, max={max}')\n", | |
" print(f',but working!')\n", | |
" edge = cv2.Canny(img,\n", | |
" min,\n", | |
" max)\n", | |
" cv2_imshow(edge)\n", | |
" print('ok!')\n", | |
"\n", | |
"\n", | |
"interact(f, min=min_slide, max=max_slide)\n", | |
"\n" | |
], | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 438, | |
"referenced_widgets": [ | |
"8848e51e746242babd4dc05d8583a176", | |
"ee5e3581159b4157a74603b5c15924be", | |
"84e5ad8017cf46f4a17ea48bb97de8fa", | |
"86bcff8f14fe4e829ee5954fda21c0a5", | |
"2bed0e04c4e94a9490a85ac16213d3ed", | |
"41f63bc6783b4af181e4303f5f68a18b", | |
"8dd98c92a5794b5e9db5848548ca4ccf", | |
"01686b9cdcc2416c83c5c066d0bc86c8", | |
"450b5dca331847ff85c2353fa5432698", | |
"09eedbb8a2bb4785a19f3bec50ba65a2" | |
] | |
}, | |
"id": "ZwMqS9eC0OGN", | |
"outputId": "b9386a63-cafb-4a8f-9db7-76cb74177515" | |
}, | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "display_data", | |
"data": { | |
"text/plain": [ | |
"interactive(children=(IntSlider(value=90, description='min', max=255), IntSlider(value=100, description='max',…" | |
], | |
"application/vnd.jupyter.widget-view+json": { | |
"version_major": 2, | |
"version_minor": 0, | |
"model_id": "8848e51e746242babd4dc05d8583a176" | |
} | |
}, | |
"metadata": {} | |
}, | |
{ | |
"output_type": "execute_result", | |
"data": { | |
"text/plain": [ | |
"<function __main__.f(min, max)>" | |
] | |
}, | |
"metadata": {}, | |
"execution_count": 23 | |
} | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [], | |
"metadata": { | |
"id": "ueFo2QzQ0hXN" | |
}, | |
"execution_count": null, | |
"outputs": [] | |
} | |
] | |
} |
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