{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import urllib.request, json\n", "import numpy as np\n", "import pandas as pd\n", "import os\n", "import requests\n", "import cv2\n", "import json\n", "from urllib.request import urlopen\n", "from skimage.metrics import structural_similarity as compare_ssim" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Load data" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv('NFT+Hackathon+Traits+Dataset.csv')" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 0collectioncontracttoken_idnft_urltrait_typevalue
69599844430pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88886https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...BackgroundBlue
69599944431pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88886https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...SkinNormal
69600044432pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88886https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...BodyHawaiian Shirt
69600144433pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88886https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...FaceHandlebar Bear
69600244434pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88886https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...HeadBucket Hat Green
69600344435pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88887https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...BackgroundBlue
69600444436pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88887https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...SkinOlive Green
69600544437pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88887https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...BodyPuffer Green
69600644438pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88887https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...FaceHandlebar Bear
69600744439pudgy_penguins0xbd3531da5cf5857e7cfaa92426877b022e612cf88887https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj...HeadFlat Cap Tan
\n", "
" ], "text/plain": [ " Unnamed: 0 collection \\\n", "695998 44430 pudgy_penguins \n", "695999 44431 pudgy_penguins \n", "696000 44432 pudgy_penguins \n", "696001 44433 pudgy_penguins \n", "696002 44434 pudgy_penguins \n", "696003 44435 pudgy_penguins \n", "696004 44436 pudgy_penguins \n", "696005 44437 pudgy_penguins \n", "696006 44438 pudgy_penguins \n", "696007 44439 pudgy_penguins \n", "\n", " contract token_id \\\n", "695998 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8886 \n", "695999 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8886 \n", "696000 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8886 \n", "696001 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8886 \n", "696002 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8886 \n", "696003 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8887 \n", "696004 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8887 \n", "696005 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8887 \n", "696006 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8887 \n", "696007 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8887 \n", "\n", " nft_url trait_type \\\n", "695998 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Background \n", "695999 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Skin \n", "696000 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Body \n", "696001 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Face \n", "696002 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Head \n", "696003 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Background \n", "696004 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Skin \n", "696005 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Body \n", "696006 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Face \n", "696007 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Head \n", "\n", " value \n", "695998 Blue \n", "695999 Normal \n", "696000 Hawaiian Shirt \n", "696001 Handlebar Bear \n", "696002 Bucket Hat Green \n", "696003 Blue \n", "696004 Olive Green \n", "696005 Puffer Green \n", "696006 Handlebar Bear \n", "696007 Flat Cap Tan " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.tail(10)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "https://ikzttp.mypinata.cloud/ipfs/QmQFkLSQysj94s5GvTHPyzTxrawwtjgiiYS2TBLgrvw8CW/1\n" ] } ], "source": [ "print(df.iloc[7]['nft_url'])" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['Unnamed: 0', 'collection', 'contract', 'token_id', 'nft_url',\n", " 'trait_type', 'value'],\n", " dtype='object')" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.keys()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create database of small size images" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "image_data = {}\n", "for ix, row in df.iloc[: 1000].iterrows():\n", " try:\n", " data_url = row['nft_url']\n", " r = requests.get(data_url)\n", " image_name = str(row['collection']) + '_' + str(row['token_id'])\n", " image_url = r.json()['image']\n", " image_data.setdefault(image_name, image_url)\n", " except Exception as e:\n", " print(e)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "for image_name, image_url in image_data.items():\n", " try:\n", " user_agent = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.9.0.7) Gecko/2009021910 Firefox/3.0.7'\n", " headers={'User-Agent':user_agent,} \n", "\n", " request=urllib.request.Request(image_url,None,headers) #The assembled request\n", " response = urllib.request.urlopen(request)\n", " \n", "# resp = urlopen(image_url)\n", " image = np.asarray(bytearray(response.read()), dtype=\"uint8\")\n", " image = cv2.imdecode(image, cv2.IMREAD_COLOR)\n", " img_path = './images1/' + str(image_name) + '.jpg'\n", "# print(img.shape)\n", " img_resized = cv2.resize(image, (64, 64), interpolation = cv2.INTER_AREA)\n", " cv2.imwrite(img_path, img_resized)\n", " except Exception as e:\n", " print(e)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Test image" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "https://ikzttp.mypinata.cloud/ipfs/QmYDvPAXtiJg7s8JdRBSLWdgSphQdac8j1YuQNNxcGE1hg/13.png\n" ] } ], "source": [ "ex_url = df.iloc[100]['nft_url']\n", "r = requests.get(ex_url)\n", "print(r.json()['image'])\n", "image_url = r.json()['image']\n", "user_agent = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.9.0.7) Gecko/2009021910 Firefox/3.0.7'\n", "headers={'User-Agent':user_agent,} \n", "\n", "request=urllib.request.Request(image_url,None,headers) #The assembled request\n", "response = urllib.request.urlopen(request)\n", "# resp = urlopen(image_url , timeout=10)\n", "image = np.asarray(bytearray(response.read()), dtype=\"uint8\")\n", "test_image = cv2.imdecode(image, cv2.IMREAD_COLOR)\n", "img_resized = cv2.resize(test_image, (500, 500), interpolation = cv2.INTER_AREA)\n", "cv2.imshow('img_resized', img_resized)\n", "cv2.waitKey() & 0xFF == ord('q')\n", "cv2.destroyAllWindows()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Find the test image in database" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.9905571084662425 azuki_13.jpg\n" ] } ], "source": [ "test_image_resized = cv2.resize(test_image, (64, 64), interpolation = cv2.INTER_AREA)\n", "ssim_list = []\n", "for image_name in os.listdir('./images1'):\n", " img = cv2.imread('./images1/' + image_name)\n", " ssim = compare_ssim(img, test_image_resized, multichannel=True)\n", " ssim_list.append(ssim)\n", "print(max(ssim_list), os.listdir('./images1')[ssim_list.index(max(ssim_list))])" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Unnamed: 0 collection \\\n", "695343 43775 pudgy_penguins \n", "695344 43776 pudgy_penguins \n", "695345 43777 pudgy_penguins \n", "695346 43778 pudgy_penguins \n", "695347 43779 pudgy_penguins \n", "\n", " contract token_id \\\n", "695343 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8755 \n", "695344 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8755 \n", "695345 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8755 \n", "695346 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8755 \n", "695347 0xbd3531da5cf5857e7cfaa92426877b022e612cf8 8755 \n", "\n", " nft_url trait_type \\\n", "695343 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Background \n", "695344 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Skin \n", "695345 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Body \n", "695346 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Face \n", "695347 https://ipfs.io/ipfs/QmWXJXRdExse2YHRY21Wvh4pj... Head \n", "\n", " value \n", "695343 Blue \n", "695344 Normal \n", "695345 Overalls \n", "695346 Circle Glasses \n", "695347 Grizzly Bear Hat \n" ] } ], "source": [ "image_url = os.listdir('./images')[ssim_list.index(max(ssim_list))].split('.')[0]\n", "if max(ssim_list) > 0.9:\n", " collection = '_'.join(os.listdir('./images')[ssim_list.index(max(ssim_list))].split('.')[0].split('_')[: -1])\n", " token_id = os.listdir('./images')[ssim_list.index(max(ssim_list))].split('.')[0].split('_')[-1]\n", " info = df[(df['collection'] == collection) & (df['token_id'] == int(token_id))]\n", " print(info)\n", "else:\n", " print('Image is not from dataset.')" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "df_sales = pd.read_csv('NFT+Hackathon+Sales+Dataset.csv')" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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blockNumbertimeStamphashfromcontractAddresstotokenIDtokenNametokenSymbolgasPricecurrencyamountamountUsd
4313981447339316484529960xa0742c124b822bab20b0b85436ce781b62327eb863e8...0x8b4ad8680a98b3dc0210eb4f21a69124211346e50x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b0x9cfb3e1c528253dcb1754a266f9f95540b41e44617241CloneXCloneX21145077548ETH14.9949797.533594
4313991447355316484550500x480a70e101ad4516226baa0514594540f22c4fe26901...0x55c05c91a859493a8b3a1017269ca706e0feb3440x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b0xc9b77effa94b599f326c3d76641f63f0979b4c677254CloneXCloneX21820224805ETH0.000.000000
4314001447355816484551300xdad0473a6aa703d5c1bc1d2bdcee6df07991e65eecc3...0xf0c55da3a8274f6843434df0da437ed4ac0dd3100x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b0xf2e03bb3bae583d72d750b3ef443372f92cf2c249303CloneXCloneX23763705682ETH0.000.000000
4314011447360616484556810x82aa9c3f16b9b5d440325fb09d5004e8a514a2003e03...0xeef2c87291d8b74537260339f50fbc1f53b6a6600x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b0xa5ee824f94abb9e3dc037815cc4727f76ab851d41818CloneXCloneX23771779965ETH0.000.000000
4314021447363716484561490x16cefb107a731b767d1e4eded3f3b3f81986506f2e9b...0x00cd05371a28d91ef833016f2aeceed5defd95e00x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b0x47da18cff5533b95435d6ee0ed8179f5daadac2413596CloneXCloneX21262054721ETH0.000.000000
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" ], "text/plain": [ " blockNumber timeStamp \\\n", "431398 14473393 1648452996 \n", "431399 14473553 1648455050 \n", "431400 14473558 1648455130 \n", "431401 14473606 1648455681 \n", "431402 14473637 1648456149 \n", "\n", " hash \\\n", "431398 0xa0742c124b822bab20b0b85436ce781b62327eb863e8... \n", "431399 0x480a70e101ad4516226baa0514594540f22c4fe26901... \n", "431400 0xdad0473a6aa703d5c1bc1d2bdcee6df07991e65eecc3... \n", "431401 0x82aa9c3f16b9b5d440325fb09d5004e8a514a2003e03... \n", "431402 0x16cefb107a731b767d1e4eded3f3b3f81986506f2e9b... \n", "\n", " from \\\n", "431398 0x8b4ad8680a98b3dc0210eb4f21a69124211346e5 \n", "431399 0x55c05c91a859493a8b3a1017269ca706e0feb344 \n", "431400 0xf0c55da3a8274f6843434df0da437ed4ac0dd310 \n", "431401 0xeef2c87291d8b74537260339f50fbc1f53b6a660 \n", "431402 0x00cd05371a28d91ef833016f2aeceed5defd95e0 \n", "\n", " contractAddress \\\n", "431398 0x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b \n", "431399 0x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b \n", "431400 0x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b \n", "431401 0x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b \n", "431402 0x49cf6f5d44e70224e2e23fdcdd2c053f30ada28b \n", "\n", " to tokenID tokenName \\\n", "431398 0x9cfb3e1c528253dcb1754a266f9f95540b41e446 17241 CloneX \n", "431399 0xc9b77effa94b599f326c3d76641f63f0979b4c67 7254 CloneX \n", "431400 0xf2e03bb3bae583d72d750b3ef443372f92cf2c24 9303 CloneX \n", "431401 0xa5ee824f94abb9e3dc037815cc4727f76ab851d4 1818 CloneX \n", "431402 0x47da18cff5533b95435d6ee0ed8179f5daadac24 13596 CloneX \n", "\n", " tokenSymbol gasPrice currency amount amountUsd \n", "431398 CloneX 21145077548 ETH 14.99 49797.533594 \n", "431399 CloneX 21820224805 ETH 0.00 0.000000 \n", "431400 CloneX 23763705682 ETH 0.00 0.000000 \n", "431401 CloneX 23771779965 ETH 0.00 0.000000 \n", "431402 CloneX 21262054721 ETH 0.00 0.000000 " ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_sales.tail()" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Azuki\n", " blockNumber timeStamp \\\n", "13 13988541 1641961048 \n", "\n", " hash \\\n", "13 0xc208fdb2f133bda64522fececd6518a565aaa6e8801b... \n", "\n", " from \\\n", "13 0x0000000000000000000000000000000000000000 \n", "\n", " contractAddress \\\n", "13 0xed5af388653567af2f388e6224dc7c4b3241c544 \n", "\n", " to tokenID tokenName tokenSymbol \\\n", "13 0xd45058bf25bbd8f586124c479d384c8c708ce23a 13 Azuki AZUKI \n", "\n", " gasPrice currency amount amountUsd \n", "13 144500135604 ETH 0.0 0.0 \n" ] } ], "source": [ "image_url = os.listdir('./images1')[ssim_list.index(max(ssim_list))].split('.')[0]\n", "if max(ssim_list) > 0.9:\n", " collection = '_'.join(os.listdir('./images1')[ssim_list.index(max(ssim_list))].split('.')[0].split('_')[: -1])\n", " collection = collection[0].upper() + collection[1:]\n", " print(collection)\n", " token_id = os.listdir('./images1')[ssim_list.index(max(ssim_list))].split('.')[0].split('_')[-1]\n", " info = df_sales[(df_sales['tokenName'] == collection) & (df_sales['tokenID'] == int(token_id))]\n", " print(info)\n", "else:\n", " print('Image is not from dataset.')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.9" } }, "nbformat": 4, "nbformat_minor": 2 }