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index.yaml
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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!"