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index.yaml
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examples:
- title: "quickstart"
path: "examples/quickstart.ipynb"
description: "A quickstart example for getting your feet wet with FiftyOne"
- title: "walkthrough"
path: "examples/walkthrough.ipynb"
description: "A more in-depth alternative to the quickstart that covers the basics of FiftyOne"
- title: "zilliz_advent_of_code"
path: "examples/zilliz_advent_of_code.ipynb"
description: "Welcome to FiftyOne: Zilliz Advent of Open Source Code 2023"
- title: "ai_telephone"
path: "examples/ai_telephone.ipynb"
description: "Play multimodal AI telephone with text-to-image models, image-to-text models, and Fiftyone"
- title: "clean_conceptual_captions"
path: "examples/clean_conceptual_captions.ipynb"
description: "Clean Google's Conceptual Captions Dataset with Fiftyone to train your own ControlNet"
- title: "segment_anything_openvino"
path: "examples/segment_anything_openvino.ipynb"
description: "Add object masks to a FiftyOne dataset with OpenVINO-optimized Segment Anything Model"
- title: "comparing_YOLO_and_EfficientDet"
path: "examples/comparing_YOLO_and_EfficientDet.ipynb"
description: "Compares the YOLOv4 and EfficientDet object detection models on the COCO dataset"
- title: "digging_into_coco"
path: "examples/digging_into_coco.ipynb"
description: "A simple example of how to find mistakes in your detection datasets"
- title: "deepfakes_in_politics"
path: "examples/deepfakes_in_politics.ipynb"
description: "Evaluating deepfakes using a deepfake detection algorithm and visualizing the results in FiftyOne"
- title: "emotion_recognition_presidential_debate"
path: "examples/emotion_recognition_presidential_debate.ipynb"
description: "Analyzing the 2020 US Presidential Debates using an emotion recognition model"
- title: "image_uniqueness"
path: "examples/image_uniqueness.ipynb"
description: "Using FiftyOne's image uniqueness method to analyze and extract insights from unlabeled datasets"
- title: "structured_noise_injection"
path: "examples/structured_noise_injection.ipynb"
description: "Visually exploring a method for structured noise injection in GANs from CVPR 2020"
- title: "visym_pip_175k"
path: "examples/visym_pip_175k.ipynb"
description: "Exploring the People in Public 175K Dataset from Visym Labs with FiftyOne"
- title: "wrangling_datasets"
path: "examples/wrangling_datasets.ipynb"
description: "Using FiftyOne to load, manipulate, and export datasets in common formats"
- title: "open_images_evaluation"
path: "examples/open_images_evaluation/open_images_evaluation.ipynb"
description: "Evaluating the quality of the ground truth annotations of the Open Images Dataset with FiftyOne"
- title: "working_with_feature_points"
path: "examples/working_with_feature_points.ipynb"
description: "A simple example of computing feature points for images and visualizing them in FiftyOne"
- title: "image_deduplication"
path: "examples/image_deduplication.ipynb"
description: "Find and remove duplicate images in your image datasets with FiftyOne"
- title: "hardness_for_image_classification"
path: "examples/exploring_classification_hardness.ipynb"
description: "Use the FiftyOne Brain to mine the hardest images in your classification dataset"
- title: "pytorch_detection_training"
path: "examples/pytorch_detection_training.ipynb"
description: "Using FiftyOne datasets to train a PyTorch object detection model"
- title: "pytorchvideo_model_evaluation"
path: "examples/pytorchvideo_tutorial.ipynb"
description: "Evaluate and visualize PyTorchVideo models with FiftyOne"
- title: "training_clearml_detector"
path: "examples/training_clearml_detector.ipynb"
description: "Train a model with ClearML and FiftyOne to detect DRAGONS!"
- title: "converting_tags_to_classifications"
path: "examples/convert_tags_to_classifications.ipynb"
description: "Convert classifications to tags and back to annotate them right in the FiftyOne App"
- title: "Qdrant_FiftyOne_Recipe"
path: "examples/Qdrant_FiftyOne_Recipe.ipynb"
description: "Nearest neighbor classification of embeddings with Qdrant"
- title: "armbench_defect_detection"
path: "examples/armbench_defect_detection.ipynb"
description: "Visualizing Defects in Amazon’s ARMBench Dataset Using Embeddings and OpenAI’s CLIP Model"
- title: "openvino_model_horizontal_text_detection"
path: "examples/openvino_detection_with_fiftyone.ipynb"
description: "Horizontal text detection on Total-Text Dataset using OpenVino Model"
- title: "chest_xray14"
path: "examples/chest_xray14.ipynb"
description: "Load and explore the NIH's ChestX-ray14 dataset in FiftyOne"
- title: "football_player_segmentation"
path: "examples/football_player_segmentation.ipynb"
description: "Detection and Segmentation on Football Player Segmentation Dataset using SAM"
- title: "wildme_conservation_datasets"
path: "examples/wildme_conservation_datasets.ipynb"
description: "Create a 'meta' dataset out of three WildMe conservation datasets in FiftyOne"
- title: "CLI Tips & Tricks"
path: "examples/Tips_and_Tricks_CLI.ipynb"
description: "Use FiftyOne's Command Line Interface to expedite your workflows"
- title: "Grouped Dataset Tips & Tricks"
path: "examples/Grouped\ Datasets.ipynb"
description: "Learn how to work with grouped datasets in FiftyOne"
- title: "Keypoint Tips & Tricks"
path: "examples/Keypoints.ipynb"
description: "Learn how to work with keypoint skeletons in FiftyOne"
- title: "3D Detections Tips & Tricks"
path: "examples/3D\ Detections.ipynb"
description: "Make your first 3D detection in point clouds using FiftyOne"
- title: "Heatmaps Tips & Tricks"
path: "examples/heatmaps.ipynb"
description: "Learn how to use heatmaps with a body pose estimation example"
- title: "Video Labels Tips & Tricks"
path: "examples/Video\ Labels.ipynb"
description: "Learn different label types in video datasets with ASL videos"
- title: "Tracking Datasets with FiftyOne"
path: "Tracking_Datasets.ipynb"
description: "Learn how to load and work with tracking datasets with the help of FiftyOne"
- title: "GradCam and More with FiftyOne"
path: "GradCam\ +\ More\ Tutorial.ipynb"
description: "Apply Model Explainability techniques to your workflows with FiftyOne and GradCam!"
- title: "Elderly Action Recognition - Challenge"
path: "examples/elderly_action_recognitio.ipynb"
description: "This notebook demonstrates the preparation of the GMDCSA24 dataset for the Elderly Action Recognition Challenge. It guides users through defining dataset paths, parsing action labels, categorizing activities, splitting videos into action-specific clips, and exporting the dataset in formats compatible with machine learning workflows. "