CoreMLCompare vs FaceCrop Auto

CoreMLCompare allows CoreML models to be easily compared and tested in real-time using the Vision Framework. The purpose is to seamlessly compare different models when detecting objects or quickly test your trained model, without the need to build your own test app. Features: - Import a new model either by using the pasteboard or after downloading the .mlmodel file on the device (browser download) - Change the model default name and configure a different color for it - Each model can be configured with a different minimum confidence level between 40% and 90% - Stopping specific models from detecting objects - using 4 models in parallel is quite processing-intensive - Can detect hot dogs (or bananas)

FaceCrop is an AI-powered photo utility that automatically detects and crops faces from both single images and batches of photos. Whether you upload one picture or dozens, the app quickly identifies every face present and extracts them into separate, high-quality face images. What sets FaceCrop apart is its built-in data augmentation features. After cropping, the app can automatically apply transformations such as horizontal flipping, rotation, brightness and color adjustments—allowing users to generate diverse image variations instantly. This is especially useful for profile creation, AI training datasets, character development, and more. With FaceCrop, you no longer need to manually find and crop faces or process images one by one. It saves time and effort by handling everything automatically, making it a highly practical tool for both casual users and professionals.