dataset downloaded from roboflow

README.dataset.txt

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+# baseball-detection-2 > 2023-06-02 3:09pm
+https://universe.roboflow.com/pitchtracking/baseball-detection-2
+
+Provided by a Roboflow user
+License: CC BY 4.0
+

README.md

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 ---
 license: mit
 ---
+
+# baseball-detection-2 > 2023-06-02 3:09pm
+https://universe.roboflow.com/pitchtracking/baseball-detection-2
+
+Provided by a Roboflow user
+License: CC BY 4.0
+
+
+baseball-detection-2 - v4 2023-06-02 3:09pm
+==============================
+
+This dataset was exported via roboflow.com on April 20, 2024 at 4:56 PM GMT
+
+Roboflow is an end-to-end computer vision platform that helps you
+* collaborate with your team on computer vision projects
+* collect & organize images
+* understand and search unstructured image data
+* annotate, and create datasets
+* export, train, and deploy computer vision models
+* use active learning to improve your dataset over time
+
+For state of the art Computer Vision training notebooks you can use with this dataset,
+visit https://github.com/roboflow/notebooks
+
+To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
+
+The dataset includes 4153 images.
+Baseballs are annotated in YOLOv9 format.
+
+The following pre-processing was applied to each image:
+* Auto-orientation of pixel data (with EXIF-orientation stripping)
+* Resize to 640x640 (Stretch)
+* Auto-contrast via adaptive equalization
+
+The following augmentation was applied to create 2 versions of each source image:
+* Randomly crop between 0 and 15 percent of the image
+* Random brigthness adjustment of between -25 and +25 percent
+* Random exposure adjustment of between -9 and +9 percent
+* Salt and pepper noise was applied to 5 percent of pixels

README.roboflow.txt

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+
+baseball-detection-2 - v4 2023-06-02 3:09pm
+==============================
+
+This dataset was exported via roboflow.com on April 20, 2024 at 4:56 PM GMT
+
+Roboflow is an end-to-end computer vision platform that helps you
+* collaborate with your team on computer vision projects
+* collect & organize images
+* understand and search unstructured image data
+* annotate, and create datasets
+* export, train, and deploy computer vision models
+* use active learning to improve your dataset over time
+
+For state of the art Computer Vision training notebooks you can use with this dataset,
+visit https://github.com/roboflow/notebooks
+
+To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
+
+The dataset includes 4153 images.
+Baseballs are annotated in YOLOv9 format.
+
+The following pre-processing was applied to each image:
+* Auto-orientation of pixel data (with EXIF-orientation stripping)
+* Resize to 640x640 (Stretch)
+* Auto-contrast via adaptive equalization
+
+The following augmentation was applied to create 2 versions of each source image:
+* Randomly crop between 0 and 15 percent of the image
+* Random brigthness adjustment of between -25 and +25 percent
+* Random exposure adjustment of between -9 and +9 percent
+* Salt and pepper noise was applied to 5 percent of pixels
+
+

data.yaml

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+train: ../train/images
+val: ../valid/images
+test: ../test/images
+
+nc: 1
+names: ['baseball']
+
+roboflow:
+  workspace: pitchtracking
+  project: baseball-detection-2
+  version: 4
+  license: CC BY 4.0
+  url: https://universe.roboflow.com/pitchtracking/baseball-detection-2/dataset/4