From 28c8b932563c5cfb9593d311ffe79eac111274c5 Mon Sep 17 00:00:00 2001 From: Adam Wojdyla Date: Tue, 17 May 2022 18:18:53 +0200 Subject: [PATCH] teacher jpg added --- jupyter.ipynb | 196 +++++++++++++++++++++----------------------------- teacher.jpeg | Bin 0 -> 93620 bytes 2 files changed, 83 insertions(+), 113 deletions(-) create mode 100644 teacher.jpeg diff --git a/jupyter.ipynb b/jupyter.ipynb index 0403147..85dc558 100644 --- a/jupyter.ipynb +++ b/jupyter.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 18, + "execution_count": 1, "metadata": { "pycharm": { "name": "#%%\n" @@ -13,7 +13,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/t3/dwnz0lh916ng4w7bzf0z56ym0000gn/T/ipykernel_20610/17056051.py:11: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n", + "/var/folders/t3/dwnz0lh916ng4w7bzf0z56ym0000gn/T/ipykernel_26663/17056051.py:11: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n", " from IPython.core.display import display, HTML\n" ] }, @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 2, "metadata": { "pycharm": { "name": "#%%\n" @@ -113,7 +113,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 3, "metadata": { "pycharm": { "name": "#%%\n" @@ -156,7 +156,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 4, "metadata": { "pycharm": { "name": "#%%\n" @@ -191,12 +191,7 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, + "execution_count": null, "outputs": [], "source": [ "def compress_show_gray_images(img_name,k):\n", @@ -213,28 +208,31 @@ " axes[1].set_title(\"compression ratio={:.2f}\".format(compression_ratio)+\"%\")\n", " axes[1].imshow(reconst_img,cmap='gray')\n", " axes[1].axis('off')\n", - " fig.tight_layout()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "W celu zbadania, jak jakość zrekonstruowanego obrazu zmienia się wraz z $k$ należy użyć poniższego interaktywnego widżetu." - ] - }, - { - "cell_type": "code", - "execution_count": 23, + " fig.tight_layout()\n", + " # compression rate = 100% * (k * (height + width + k)) / (height + width)" + ], "metadata": { + "collapsed": false, "pycharm": { "name": "#%%\n" } - }, + } + }, + { + "cell_type": "markdown", + "source": [ + "W celu zbadania, jak jakość zrekonstruowanego obrazu zmienia się wraz z $k$ należy użyć poniższego interaktywnego widżetu." + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%% md\n" + } + } + }, + { + "cell_type": "code", + "execution_count": null, "outputs": [], "source": [ "def compute_k_max(img_name):\n", @@ -256,20 +254,24 @@ " int_slider_widget.max = compute_k_max(img_name)\n", "\n", "list_widget.observe(update_k_max,'value')\n" - ] - }, - { - "cell_type": "code", - "execution_count": 24, + ], "metadata": { + "collapsed": false, "pycharm": { "name": "#%%\n" } - }, + } + }, + { + "cell_type": "code", + "execution_count": null, "outputs": [], "source": [ "# Print matrices\n", "def print_matrices(img_name, k):\n", + " if (img_name not in gray_images.keys()):\n", + " return\n", + " \n", " image=gray_images[img_name]\n", " original_shape = image.shape\n", " print(f\"Input image dimensions. Width:{original_shape[1]} Height:{original_shape[0]}\")\n", @@ -283,93 +285,57 @@ " print('*' * 100)\n", " print(f\"Shape of V matrix: {V[:k,:].shape}\")\n", " print(f\"V MATRIX: {V[:k,:]}\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 25, + ], "metadata": { + "collapsed": false, "pycharm": { "name": "#%%\n" } - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "97ddd455e9c8432c9d06874ef2d8d4c8", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'camera', 'coin', 'clock', 'te…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], "source": [ "interact(print_matrices, img_name=list_widget, k=int_slider_widget)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, + ], "metadata": { + "collapsed": false, "pycharm": { "name": "#%%\n" } - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "845d2b4394b04d5681141aac8e9cbc29", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'camera', 'coin', 'clock', 'te…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], "source": [ "interact(compress_show_gray_images,img_name=list_widget,k=int_slider_widget);" - ] + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "markdown", + "source": [ + "### Ładowanie kolorowych obrazów" + ], "metadata": { + "collapsed": false, "pycharm": { "name": "#%% md\n" } - }, - "source": [ - "### Ładowanie kolorowych obrazów" - ] + } }, { "cell_type": "code", - "execution_count": 27, - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, + "execution_count": null, "outputs": [], "source": [ "color_images = {\n", @@ -378,9 +344,16 @@ " \"coffee\":img_as_float(data.coffee()),\n", " \"rocket\":img_as_float(data.rocket()),\n", " \"koala\": img_as_float(Image.open('koala.jpeg')),\n", - " \"orange\": img_as_float(Image.open('orange.jpeg'))\n", - "}" - ] + " \"orange\": img_as_float(Image.open('orange.jpeg')),\n", + " \"teacher\": img_as_float(Image.open('teacher.jpeg'))\n", + "}\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } }, { "cell_type": "markdown", @@ -489,12 +462,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "704a0aea9bc64cf991168a250b20c6a7", + "model_id": "4715b532b1d64abc9a8451cbfcfcc0e7", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'koala', 'orange'), …" + "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'rocket', 'koala', '…" ] }, "metadata": {}, @@ -527,12 +500,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a952305f0af44bbb89f18df43a922d7d", + "model_id": "f56619fa4fac4a6b9babba92ed3fb72a", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'koala', 'orange'), …" + "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'rocket', 'koala', '…" ] }, "metadata": {}, @@ -629,10 +602,9 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": { "pycharm": { - "is_executing": true, "name": "#%%\n" } }, @@ -640,12 +612,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5fcf1a7a0089474db6ae5775db349344", + "model_id": 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