Real Estate Classifier - Algorithm by deeplearning

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1. Introduction This is an image classifier specifically built for Real Estate applications. Currently it classifies 17 categories: bathroom bedroom brick_house colonial_house fireplace garage g arden house_front house_gat e house_stairs kitchen_full living_room modern_house pool victorian_house walk_in_closet beach_house Input: (Required) Image Data API Url, Web (http/https) Url, binary image or a base64 encoded image. (Optional) ?Number of results. (Default=5) Output: Top N classifications. Note: The first call to this algorithm will take a bit longer than sequential calls to due algorithm initialization. All following calls will be significantly faster. 2. Examples Example 1. Parameter 1: Data API Url {
 "image": "data://deeplearning/example_data/garden.jpeg"
} Output {
 "results":[
 [0.9988620877265929,"garden"],
 [0.0007119349902495742,"brick_house"],
 [0.00032106676371768117,"colonial_house"],
 [0.00009232714364770799,"house_gate"],
 [0.000007944731805764606,"victorian_house"]
 ]
} Example 2. Parameter 1: HTTP Url {
 "image": "https://s3.amazonaws.com/algorithmia-assets/algo_desc_images/deeplearning_RealEstateClassifier/beach_house.jpeg"
} Output: {
 "results":[
 [0.969028651714325,"beach_house"],
 [0.014721000567078587,"house_stairs"],
 [0.010782225057482723,"modern_house"],
 [0.0028136796317994595,"victorian_house"],
 [0.0019394016126170757,"brick_house"]
 ]
} Example 3. Parameter 1: Base64 image {
 "image": "data:image/png;base64....",
} Output; {
 "results":[
 [0.9476951360702517,"bathroom"],
 [0.05226270481944084,"house_stairs"],
 [0.000020802997823921036,"walk_in_closet"],
 [0.000011968691978836432,"fireplace"],
 [0.000005980698006169406,"living_room"]
 ]
} Example 4. Parameter 1: Data API Url Parameter 2: Number of results. {
 "image": "data://deeplearning/example_data/pool.jpeg",
 "numResults": 10
} Output: {
 "results":[
 [0.9999868273735046,"pool"],
 [0.000009537410733173601,"beach_house"],
 [0.000003382114300620742,"garden"],
 [2.007873973752794e-7,"modern_house"],
 [1.669178928409565e-8,"garage"],
 [2.5206952081191507e-9,"house_gate"],
 [2.1088919499590024e-9,"bedroom"],
 [4.0900935416310357e-10,"brick_house"],
 [3.530754300040684e-10,"kitchen_full"],
 [3.0397151462580036e-10,"bathroom"]
 ]
} 3. Credits This classifier was trained in-house on Deep Purple. Demo image were retrieved from Unsplash: https://unsplash.com/photos/CvpWxeAEUOE

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1. Type your input

2. See the result

Running algorithm...

curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY' https://api.algorithmia.com/v1/algo/deeplearning/RealEstateClassifier/0.2.3

View cURL Docs

algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://deeplearning/RealEstateClassifier/0.2.3 -d '{{input | formatInput:"cli"}}'

View CLI Docs

import (
  algorithmia "github.com/algorithmiaio/algorithmia-go"
)

input := {{input | formatInput:"go"}}

var client = algorithmia.NewClient("YOUR_API_KEY", "")
algo, _ := client.Algo("algo://deeplearning/RealEstateClassifier/0.2.3")
resp, _ := algo.Pipe(input)
response := resp.(*algorithmia.AlgoResponse)
fmt.Println(response.Result)

View Go Docs

import com.algorithmia.*;
import com.algorithmia.algo.*;

String input = "{{input | formatInput:"java"}}";
AlgorithmiaClient client = Algorithmia.client("YOUR_API_KEY");
Algorithm algo = client.algo("algo://deeplearning/RealEstateClassifier/0.2.3");
AlgoResponse result = algo.pipeJson(input);
System.out.println(result.asJsonString());

View Java Docs

import com.algorithmia._
import com.algorithmia.algo._

val input = {{input | formatInput:"scala"}}
val client = Algorithmia.client("YOUR_API_KEY")
val algo = client.algo("algo://deeplearning/RealEstateClassifier/0.2.3")
val result = algo.pipeJson(input)
System.out.println(result.asJsonString)

View Scala Docs

var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://deeplearning/RealEstateClassifier/0.2.3")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });

View Javascript Docs

using Algorithmia;

var input = "{{input | formatInput:"cs"}}";
var client = new Client("YOUR_API_KEY");
var algorithm = client.algo("algo://deeplearning/RealEstateClassifier/0.2.3");
var response = algorithm.pipe<object>(input);
Console.WriteLine(response.result);

View .NET/C# Docs

var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://deeplearning/RealEstateClassifier/0.2.3")
           .pipe(input)
           .then(function(response) {
             console.log(response.get());
           });

View NodeJS Docs

import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('deeplearning/RealEstateClassifier/0.2.3')
print algo.pipe(input)

View Python Docs

library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("deeplearning/RealEstateClassifier/0.2.3")
result <- algo$pipe(input)$result
print(result)

View R Docs

require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('deeplearning/RealEstateClassifier/0.2.3')
puts algo.pipe(input).result

View Ruby Docs

use algorithmia::Algorithmia;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo("deeplearning/RealEstateClassifier/0.2.3");
let response = algo.pipe(input);

View Rust Docs

import Algorithmia

let input = "{{input | formatInput:"swift"}}";
let client = Algorithmia.client(simpleKey: "YOUR_API_KEY")
let algo = client.algo(algoUri: "deeplearning/RealEstateClassifier/0.2.3") { resp, error in
  print(resp)
}

View Swift Docs

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