SnapDetect - an object recognition app through image.

Developed an object recognition application for Android using TensorFlow Lite and MobileNet V3 model to identify objects through images used Retrofit for fetch data.

A real-time object recognition feature, enhancing user interaction and engagement.

Demo Video

API Reference

References:

Model: MobileNet V3 ( https://shorturl.at/VEnYT )

API: Knowledge Graph Search ( https://shorturl.at/Jlbb1 )

Dependencies

    implementation("com.github.bumptech.glide:glide:4.12.0")

    implementation("com.squareup.retrofit2:retrofit:2.9.0")
    implementation("com.squareup.retrofit2:converter-gson:2.9.0")

    implementation("org.tensorflow:tensorflow-lite:2.7.0")
    implementation("org.tensorflow:tensorflow-lite-support:0.2.0")
    implementation("org.tensorflow:tensorflow-lite-gpu:2.7.0")

Get item

import retrofit2.Call
import retrofit2.http.GET
import retrofit2.http.Query

interface KnowledgeGraphApiService {

    @GET("v1/entities:search")
    fun getEntityDetails(
        @Query("query") query: String,
        @Query("key") apiKey: String
    ): Call<KnowledgeGraphResponse>
}

Convert to GSON

    val retrofit = Retrofit.Builder()
            .baseUrl("https://kgsearch.googleapis.com/")
            .addConverterFactory(GsonConverterFactory.create())
            .build()

Features

📸 Capture images via camera

🖼️ Select images from the gallery

🌐 Use images from URLs

📤 Share images and details seamlessly

Tech Stack

Development Environment: Android Studio

Programming Language: Kotlin

Framework: TensorFlow Lite

API Integration: Knowledge Graph Search

Model: MobileNet V3

User Interface Design: Material Design Principles

Testing: Unit Testing, Integration Testing, User Testing