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geekyrakshit
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Parent(s):
2dd1081
Created using Colaboratory
Browse files- notebooks/enhance_me_train.ipynb +161 -61
notebooks/enhance_me_train.ipynb
CHANGED
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"cells": [
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"cell_type": "markdown",
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"metadata": {
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"source": [
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"<a href=\"https://colab.research.google.com/github/soumik12345/enhance-me/blob/mirnet/notebooks/enhance_me_train.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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"height": 1000
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"id": "1JryaVhtBHij",
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"outputId": "
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"outputs": [],
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"source": [
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"!git clone https://github.com/soumik12345/enhance-me -b mirnet\n",
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"!pip install wandb streamlit"
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "G_c4VtXWHR5l"
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"outputs": [],
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"source": [
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"import sys\n",
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"sys.path.append(\"./enhance-me\")\n",
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"from PIL import Image\n",
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"from enhance_me import commons\n",
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"from enhance_me.mirnet import MIRNet"
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "ZpBHbYaMIqP_"
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"outputs": [],
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"source": [
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"#@title MIRNet Train Configs\n",
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"\n",
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"experiment_name = '
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"image_size = 128 #@param {type:\"integer\"}\n",
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"dataset_label = 'lol' #@param [\"lol\"]\n",
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"apply_random_horizontal_flip = True #@param {type:\"boolean\"}\n",
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"learning_rate = 1e-4 #@param {type:\"number\"}\n",
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"epsilon = 1e-3 #@param {type:\"number\"}\n",
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"epochs = 50 #@param {type:\"slider\", min:10, max:100, step:5}"
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"id": "IVRoedqBIMuH",
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"outputs": [],
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"source": [
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"mirnet = MIRNet(\n",
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" experiment_name=experiment_name,\n",
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" image_size=image_size,\n",
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" dataset_label=dataset_label,\n",
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" val_split=val_split,\n",
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" batch_size=batch_size,\n",
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" apply_random_horizontal_flip=apply_random_horizontal_flip,\n",
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" apply_random_vertical_flip=apply_random_vertical_flip,\n",
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" apply_random_rotation=apply_random_rotation,\n",
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"execution_count": null,
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"metadata": {
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"id": "tsfKrBCsL_Bb"
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"outputs": [],
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"source": [
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"mirnet.build_model(\n",
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" num_recursive_residual_groups=num_recursive_residual_groups,\n",
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" learning_rate=learning_rate,\n",
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" epsilon=epsilon\n",
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")"
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"execution_count": null,
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"metadata": {
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"base_uri": "https://localhost:8080/"
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"id": "y3L9wlpkNziL",
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"outputs": [],
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"source": [
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"history = mirnet.train(epochs=epochs)"
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},
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"outputs": [],
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"source": [
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"for index, low_image_file in enumerate(mirnet.test_low_images):\n",
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" original_image = Image.open(low_image_file)\n",
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" [\"Original Image\", \"Ground Truth\", \"Enhanced Image\"],\n",
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" (18, 18)\n",
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" )"
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"accelerator": "GPU",
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"include_colab_link": true,
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"machine_shape": "hm",
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"name": "enhance-me-train.ipynb",
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"name": "enhance-me-train.ipynb",
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"cells": [
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"cell_type": "markdown",
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"id": "view-in-github",
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"colab_type": "text"
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"source": [
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"<a href=\"https://colab.research.google.com/github/soumik12345/enhance-me/blob/mirnet/notebooks/enhance_me_train.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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},
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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"id": "1JryaVhtBHij",
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"outputId": "97ee6a4a-2479-4124-e96a-f0a792bdec46"
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},
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"source": [
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"!git clone https://github.com/soumik12345/enhance-me -b mirnet\n",
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"!pip install -qqq wandb streamlit"
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],
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"execution_count": 1,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Cloning into 'enhance-me'...\n",
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"remote: Enumerating objects: 89, done.\u001b[K\n",
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"remote: Counting objects: 100% (89/89), done.\u001b[K\n",
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"remote: Compressing objects: 100% (61/61), done.\u001b[K\n",
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"remote: Total 89 (delta 43), reused 63 (delta 23), pack-reused 0\u001b[K\n",
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"Unpacking objects: 100% (89/89), done.\n",
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"\u001b[K |████████████████████████████████| 1.7 MB 8.2 MB/s \n",
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"\u001b[K |████████████████████████████████| 9.1 MB 33.4 MB/s \n",
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"\u001b[K |████████████████████████████████| 140 kB 74.7 MB/s \n",
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"\u001b[K |████████████████████████████████| 97 kB 8.6 MB/s \n",
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"\u001b[K |████████████████████████████████| 180 kB 83.6 MB/s \n",
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"\u001b[K |████████████████████████████████| 63 kB 2.1 MB/s \n",
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"\u001b[K |████████████████████████████████| 4.3 MB 83.4 MB/s \n",
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"\u001b[K |████████████████████████████████| 178 kB 68.0 MB/s \n",
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"\u001b[K |████████████████████████████████| 76 kB 6.0 MB/s \n",
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"\u001b[K |████████████████████████████████| 111 kB 81.8 MB/s \n",
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"\u001b[K |████████████████████████████████| 125 kB 86.7 MB/s \n",
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"\u001b[K |████████████████████████████████| 791 kB 67.2 MB/s \n",
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"\u001b[K |████████████████████████████████| 374 kB 83.4 MB/s \n",
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"\u001b[?25h Building wheel for subprocess32 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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" Building wheel for pympler (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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" Building wheel for blinker (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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" Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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"\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
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"jupyter-console 5.2.0 requires prompt-toolkit<2.0.0,>=1.0.0, but you have prompt-toolkit 3.0.23 which is incompatible.\n",
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"google-colab 1.0.0 requires ipykernel~=4.10, but you have ipykernel 6.5.1 which is incompatible.\n",
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"google-colab 1.0.0 requires ipython~=5.5.0, but you have ipython 7.30.0 which is incompatible.\u001b[0m\n"
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]
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}
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{
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"cell_type": "code",
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"metadata": {
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"id": "G_c4VtXWHR5l"
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},
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"source": [
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"import sys\n",
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"sys.path.append(\"./enhance-me\")\n",
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"from PIL import Image\n",
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"from enhance_me import commons\n",
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"from enhance_me.mirnet import MIRNet"
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],
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"execution_count": 2,
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"outputs": []
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{
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"cell_type": "code",
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"metadata": {
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"id": "ZpBHbYaMIqP_"
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},
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"source": [
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"#@title MIRNet Train Configs\n",
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"\n",
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"experiment_name = 'lol_dataset_256' #@param {type:\"string\"}\n",
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"image_size = 128 #@param {type:\"integer\"}\n",
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"dataset_label = 'lol' #@param [\"lol\"]\n",
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"apply_random_horizontal_flip = True #@param {type:\"boolean\"}\n",
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"learning_rate = 1e-4 #@param {type:\"number\"}\n",
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"epsilon = 1e-3 #@param {type:\"number\"}\n",
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"epochs = 50 #@param {type:\"slider\", min:10, max:100, step:5}"
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],
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"execution_count": 3,
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"outputs": []
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},
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 52
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},
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"id": "IVRoedqBIMuH",
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"outputId": "53ca5beb-871a-4ec3-b757-173e09a15331"
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},
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"source": [
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"mirnet = MIRNet(\n",
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" experiment_name=experiment_name,\n",
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" wandb_api_key=None if wandb_api_key == '' else wandb_api_key\n",
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")"
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],
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"execution_count": 4,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33m19soumik-rakshit96\u001b[0m (use `wandb login --relogin` to force relogin)\n"
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]
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},
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{
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"output_type": "display_data",
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"data": {
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"text/html": [
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"\n",
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" Syncing run <strong><a href=\"https://wandb.ai/19soumik-rakshit96/mirnet/runs/3p3rc341\" target=\"_blank\">lol_dataset_256</a></strong> to <a href=\"https://wandb.ai/19soumik-rakshit96/mirnet\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">docs</a>).<br/>\n",
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"\n",
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],
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"text/plain": [
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"metadata": {}
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"cell_type": "code",
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"metadata": {
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"base_uri": "https://localhost:8080/"
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},
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},
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"source": [
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"mirnet.build_datasets(\n",
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" image_size=image_size,\n",
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" dataset_label=dataset_label,\n",
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" apply_random_horizontal_flip=apply_random_horizontal_flip,\n",
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" apply_random_vertical_flip=apply_random_vertical_flip,\n",
|
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" apply_random_rotation=apply_random_rotation,\n",
|
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+
" val_split=val_split,\n",
|
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+
" batch_size=batch_size\n",
|
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")"
|
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+
],
|
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+
"execution_count": 5,
|
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+
"outputs": [
|
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+
{
|
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+
"output_type": "stream",
|
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+
"name": "stdout",
|
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+
"text": [
|
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+
"Downloading data from https://github.com/soumik12345/enhance-me/releases/download/v0.1/lol_dataset.zip\n",
|
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+
"347176960/347171015 [==============================] - 13s 0us/step\n",
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"347185152/347171015 [==============================] - 13s 0us/step\n",
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"Number of train data points: 436\n",
|
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"Number of validation data points: 49\n"
|
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]
|
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}
|
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|
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},
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{
|
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"cell_type": "code",
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"metadata": {
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"id": "tsfKrBCsL_Bb"
|
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},
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"source": [
|
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"mirnet.build_model(\n",
|
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" num_recursive_residual_groups=num_recursive_residual_groups,\n",
|
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" learning_rate=learning_rate,\n",
|
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" epsilon=epsilon\n",
|
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")"
|
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+
],
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+
"execution_count": 6,
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"outputs": []
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
|
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"base_uri": "https://localhost:8080/"
|
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},
|
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"id": "y3L9wlpkNziL",
|
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+
"outputId": "5149f0e7-91f4-450f-c43a-1b6028692bbc"
|
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},
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"source": [
|
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"history = mirnet.train(epochs=epochs)"
|
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+
],
|
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"execution_count": null,
|
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+
"outputs": [
|
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+
{
|
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+
"output_type": "stream",
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"name": "stderr",
|
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+
"text": [
|
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+
"/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py:1410: CustomMaskWarning: Custom mask layers require a config and must override get_config. When loading, the custom mask layer must be passed to the custom_objects argument.\n",
|
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+
" layer_config = serialize_layer_fn(layer)\n"
|
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+
]
|
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+
},
|
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+
{
|
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+
"output_type": "stream",
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"name": "stdout",
|
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+
"text": [
|
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+
"Epoch 1/50\n",
|
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+
" 66/218 [========>.....................] - ETA: 2:25 - loss: 0.1721 - peak_signal_noise_ratio: 63.2555"
|
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]
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}
|
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|
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},
|
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{
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"cell_type": "code",
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"metadata": {
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"colab": {
|
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"background_save": true
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},
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"id": "daFKbgBkiyzc"
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},
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"source": [
|
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"for index, low_image_file in enumerate(mirnet.test_low_images):\n",
|
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" original_image = Image.open(low_image_file)\n",
|
|
|
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" [\"Original Image\", \"Ground Truth\", \"Enhanced Image\"],\n",
|
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" (18, 18)\n",
|
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" )"
|
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+
],
|
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"execution_count": null,
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"outputs": []
|
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{
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"cell_type": "code",
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"metadata": {
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"id": "dO-IbNQHkB3R"
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+
"source": [
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+
""
|
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+
],
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"execution_count": null,
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"outputs": []
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}
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