에 의해 게시 Joao Frasco
1. The eight models include: AgeNet (that classifies the age of the human subject); GenderNet (that classifies the gender of the subject); CNN Emotions (that classifies the emotion of the person); VisualSentiment (that classifies the human subject's sentiment as positive or negative); Food101 (that classifies the food), Oxford102 (that classifies flowers); CarRecognition (that classifies the make of car); and GoogLeNetPlaces (that classifies the category of place in the image).
2. MLFotoFun uses state of the art Machine Learning models that use Convolutional Neural Networks (CNNs) to classify photos taken with your camera or from your library using one of eight state of the art models.
3. This app is for entertainment purposes only, and clearly demonstrates how bad such models can be, as well as the biases that they may contain, so no offence is intended with age or gender classification.
4. The classification includes the two most probable descriptive labels, as well as the probability associated with each label.
5. It may however also surprise you in how far image recognition has come in the five years.
또는 아래 가이드를 따라 PC에서 사용하십시오. :
PC 버전 선택:
소프트웨어 설치 요구 사항:
직접 다운로드 가능합니다. 아래 다운로드 :
설치 한 에뮬레이터 애플리케이션을 열고 검색 창을 찾으십시오. 일단 찾았 으면 MLFotoFun 검색 막대에서 검색을 누릅니다. 클릭 MLFotoFun응용 프로그램 아이콘. 의 창 MLFotoFun Play 스토어 또는 앱 스토어의 스토어가 열리면 에뮬레이터 애플리케이션에 스토어가 표시됩니다. Install 버튼을 누르면 iPhone 또는 Android 기기 에서처럼 애플리케이션이 다운로드되기 시작합니다. 이제 우리는 모두 끝났습니다.
"모든 앱 "아이콘이 표시됩니다.
클릭하면 설치된 모든 응용 프로그램이 포함 된 페이지로 이동합니다.
당신은 아이콘을 클릭하십시오. 그것을 클릭하고 응용 프로그램 사용을 시작하십시오.
다운로드 MLFotoFun Mac OS의 경우 (Apple)
다운로드 | 개발자 | 리뷰 | 평점 |
---|---|---|---|
$0.99 Mac OS의 경우 | Joao Frasco | 0 | 1 |
MLFotoFun uses state of the art Machine Learning models that use Convolutional Neural Networks (CNNs) to classify photos taken with your camera or from your library using one of eight state of the art models. The classification includes the two most probable descriptive labels, as well as the probability associated with each label. The eight models include: AgeNet (that classifies the age of the human subject); GenderNet (that classifies the gender of the subject); CNN Emotions (that classifies the emotion of the person); VisualSentiment (that classifies the human subject's sentiment as positive or negative); Food101 (that classifies the food), Oxford102 (that classifies flowers); CarRecognition (that classifies the make of car); and GoogLeNetPlaces (that classifies the category of place in the image). This app is for entertainment purposes only, and clearly demonstrates how bad such models can be, as well as the biases that they may contain, so no offence is intended with age or gender classification. It may however also surprise you in how far image recognition has come in the five years.
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