Hand-drawn Power Converter Circuit Diagrams

Citation Author(s):
University of Houston
Harish S.
University of Houston
Submitted by:
Bharat Bohara
Last updated:
Wed, 01/24/2024 - 17:26
Data Format:
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The dataset is created on June 8, 2023, at 12:28 AM, consists of 760 annotated images in Pascal VOC format. The dataset was exported via roboflow.com, an end-to-end computer vision platform that facilitates various tasks such as collaboration, image collection and organization, data understanding and search, annotation, dataset creation, model training and deployment, and active learning for dataset improvement. Each image in the dataset underwent pre-processing, which involved auto-orienting the pixel data by removing EXIF orientation, and resizing the images to a uniform size of 640x640 pixels through stretching. To increase the dataset's diversity and variability, the following augmentations were applied to generate five versions of each source image: horizontal flip (50% probability), vertical flip (50% probability), 90-degree rotations (none, clockwise, counter-clockwise, upside-down with equal probability), random rotation (-15 to +15 degrees), random shear (-15° to +15° horizontally and vertically), random brightness adjustment (-25% to +25%), random exposure adjustment (-25% to +25%), random Gaussian blur (0 to 1.25 pixels), and the application of salt and pepper noise to 3% of the pixels. Researchers and developers can utilize this dataset and access state-of-the-art computer vision training.



myHD-ECD - v1 2023-06-08 12:28am



This dataset was exported via roboflow.com on June 8, 2023 at 5:30 AM GMT


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visit https://github.com/roboflow/notebooks


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The dataset includes 760 images.

Components are annotated in Pascal VOC format.


The following pre-processing was applied to each image:

* Auto-orientation of pixel data (with EXIF-orientation stripping)

* Resize to 640x640 (Stretch)


The following augmentation was applied to create 5 versions of each source image:

* 50% probability of horizontal flip

* 50% probability of vertical flip

* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down

* Random rotation of between -15 and +15 degrees

* Random shear of between -15° to +15° horizontally and -15° to +15° vertically

* Random brigthness adjustment of between -25 and +25 percent

* Random exposure adjustment of between -25 and +25 percent

* Random Gaussian blur of between 0 and 1.25 pixels

* Salt and pepper noise was applied to 3 percent of pixels