Calorieasy

#1 Product of the WeekHealth & Fitness#5 Product of the DayProduct HuntTrack calories in seconds with AISnap a photo to get instant calories and macrosAI automatically logs meals date and time Track your progress and achieve your fitness goals#1 AI calorie tracker app!Previously used by 5000+ healthier usersApp is no longer active SponsoredNeed a professional LinkedIn photo?Rated 4.8/5 from 3,013 reviews onLook professional without leaving home14× more likely to get hiredStudio-quality headshots in minutesGet professional headshotsReviewsHappy reviews from happier clientsJessica H.I've been using this AI calorie tracker for a abit now, and it's been an absolute game-changer for me. The simplicity of just taking a picture is beautiful! There were some problems but I sent an email and instantly got help. Anita G.I've tried several calorie-counting apps, but this is by far the most innovative. The AI technology is impressive; it recognizes almost every dish I've snapped so far.Marcus T.Never thought I'd say this, but tracking calories is kinda fun now, good job!Alice R.This app has changed my life! I've tried many, but this one makes calorie counting so much easier. Highly recommend!Johan D.As someone who's into fitness, this app has made it super simple to keep track of my progress. Love it!Isabella K.I was hesitant at first, but the app's interface is so intuitive. Even a beginner like me finds it easy to use.Leonardo M.I've tried similar apps before, but none come close to this one. It's fast, reliable, and looks great!Mei L.Great app! The calorie tracking is on point, and I love the feature that gives me a daily breakdown of my nutrition.Samir N.I'm really impressed! The app does everything I need without being too complicated. Perfect for busy people like me.PricingCalorieasy ProTrack less & live more!$69For a whole year of accessPackage includes:Unlimited scansHighest accuracyFastest counting speedMacros breakdownWeekly chartPriority SupportGet Calorieasy ProFAQsFrequently Asked QuestionsWhat is Calorieasy?Calorieasy is a health and fitness app designed to help you track your calorie intake with the power of AI.The app allows you to log meals, track your calories, and set personal health goals.It integrates with various fitness devices and apps to provide a comprehensive overview of your health and fitness data.How does Calorieasy track my calories?Calorieasy uses our flagship AI model Avoquadro to analyze the calories within a photo that you take.Is Calorieasy available on multiple devices?Yes, Calorieasy is available on both iOS and Android devices.How can I get support if I have issues with the app?If you encounter any issues or have questions about Calorieasy, you can reach out to our support team contact@calorieasy.appHow much is the Pro version?$9.99/month and $69.99/year for Pro features.What does Pro version include?Unlimited access to Calorieasy's premium features, including advanced analytics.What is the refund policy?Our refund policy is customer-oriented and straightforward. We process all refund requests promptly, no questions asked. We strive to ensure complete customer satisfaction and a hassle-free experience.What payment methods are available?We accept payments through trusted and secure platforms - Stripe.Calorieasy or our support team will never request any payment details directly. Instead, we provide official payment links through our website.Will I receive an invoice for my purchase?Absolutely! We provide an invoice for all purchases made through our platform. The invoice will be sent directly to the email address associated with your account, ensuring transparency and record-keeping.Does Calorieasy collect personal data?Yes, Calorieasy collects strictly necessary personal data, specifically email addresses and personal stats. 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beloved avocado mascot of the Calorieasy app and the powerful NVIDIA Quadro GPU that facilitated its training. Full disclosure: I am an indie hacker, and my only experience with machine learning and neural networks is derived from a single semester at university. Despite not being an expert, I've devoted significant time and effort to developing Avoquadro. By combining the strengths of several vision models and my own custom model, Avoquadro is able to enhance food image classification and serve as the backbone of Calorieasy's comprehensive calorie tracking technology.Related WorkAvoquadro builds upon a rich history of food image classification models. Notable among these is the Food-101 dataset, which has been widely used in various research projects. The dataset, introduced by Bossard et al. (2014), consists of 101,000 images spread across 101 categories, providing a robust foundation for training and evaluating food classification models. Additionally, models like DeepFood have demonstrated the potential of deep learning techniques in achieving high accuracy in food recognition tasks. DeepFood, for instance, achieved a notable accuracy of 77.4% on the Food-101 dataset, setting a benchmark for subsequent models. By leveraging advancements in convolutional neural networks (CNNs) and integrating state-of-the-art vision models, Avoquadro aims to push the boundaries further, ensuring more accurate and reliable food classification results.MethodologyAvoquadro's development involved a meticulous combination of various vision models and custom neural networks to optimize performance and accuracy. The model's architecture integrates the following key components:Efficient Parameters: The model's design focuses on maintaining an optimal number of parameters to ensure efficient execution on platforms like Replicate. This approach helps in reducing computational costs and offering competitive pricing to users.Depth Accuracy: Avoquadro incorporates advanced techniques to account for depth and distance in image analysis. By utilizing depth information, the model enhances its ability to accurately identify and classify different food items, considering their spatial characteristics.Speed: Emphasis on speed optimization ensures that Avoquadro delivers quick and responsive results, enhancing the overall user experience. The model's architecture is designed to process images swiftly, making it suitable for real-time applications.Robust Training: The model was trained on the Food-101 dataset, which includes 101,000 images across 101 food categories. This extensive dataset provided a diverse and comprehensive training ground for Avoquadro, ensuring its robustness and generalizability.MetricsTo evaluate the performance of Avoquadro, we employed common metrics used in food image classification models:Accuracy: The percentage of correctly classified images out of the total number of images.Precision: The ratio of true positive predictions to the sum of true positive and false positive predictions, indicating the accuracy of the model's positive predictions.Recall: The ratio of true positive predictions to the sum of true positive and false negative predictions, indicating the model's ability to identify all relevant instances.F1 Score: The harmonic mean of precision and recall, providing a single metric that balances both precision and recall.Top-5 Accuracy: The percentage of images where the correct label is among the top five predictions made by the model. This metric is particularly useful in scenarios where multiple similar food items are present.By leveraging these metrics, we ensured a comprehensive evaluation of Avoquadro's performance, highlighting its strengths and identifying areas for further improvement.Conclusion Avoquadro wields impressive results and surpasses expectations for the majority of Calorieasy users. Its performance is more than enough to satisfy my customers. Naturally, I can't reveal all the secrets—after all, it's what gives me the competitive edge over my competitors! Also kind of writing this because my old professor insisted I adopt a more formal tone in documenting my models, ensuring my hard work doesn't go unnoticed. Finally, I hope to continue improving the model to enhance its capabilities and provide even better support for our users.