dataset uploaded by roboflow2huggingface package

README.dataset.txt

@@ -1,30 +1,18 @@
-# undefined > raw images
-https://public.roboflow.ai/object-detection/undefined
+# Construction Site Safety > original_raw-images
+https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety
 
-Provided by undefined
+Provided by a Roboflow user
 License: CC BY 4.0
 
-# SkyBot
-
-This is the dataset powering http://skybot.cam, an app that captures planes flying over top of my house.
-
-![Skycam Tweet](https://i.imgur.com/DhxlR8J.png)
-
-Upon the project gaining popularity on [Hacker News](https://news.ycombinator.com/item?id=30039597) from the above [tweet](https://twitter.com/LukeBerndt/status/1484916000139194375), I thought I'd share the dataset and an example model to make it easier for others to build a plane spotting app, too.
-
-## About this Project
-I built a system to take photos of all of the airplanes that fly over my house. Most of these planes are passing by at more than 30,000 feet! It uses ADS-B to track where the aircraft are relative to the camera, points the camera in the right direction and snaps a photo. I then run a few serverless functions that are running to detect where the aircraft is in the image and make a thumbnail. Much of the services are hosted on Azure. There's more details on the overall project here! http://skybot.cam/about. The project is [open source](https://github.com/IQTLabs/SkyScan/tree/main/ml-model/scripts) as a part of my work from IQT as well.
-
-
-![Skybot Infrastructure](https://i.imgur.com/Lrv71Aq.png)
-
-
-## About the Dataset
-The dataset is of airfract that was captured as they flew overhead. It includes a mix of large and small passenger jets and an assortment of business jets. There are also a images with buildings and contrails, where there is not aircraft present.
-
-### Use Cases
-
-This dataset should allow for a plane dectector model to be built like for plane spotting and plane detection. 
-
-## About Me
-I'm Luke Berndt, I work on Azure products at Microsoft. You can learn more about me here: http://lukeberndt.com/
+videos from:
+* https://www.youtube.com/watch?v=Dhxf5mm7g1g
+* https://www.youtube.com/watch?v=rYv9JZ2XBW4
+
+images cloned from:
+* https://universe.roboflow.com/roboflow-universe-projects/personal-protective-equipment-combined-model/
+* https://universe.roboflow.com/roboflow-universe-projects/people-and-ladders/
+* https://universe.roboflow.com/roboflow-universe-projects/safety-vests/
+* https://universe.roboflow.com/mohamed-sabek-6zmr6/excavators-cwlh0
+* https://universe.roboflow.com/popular-benchmarks/mit-indoor-scene-recognition/ - null images
+* https://universe.roboflow.com/mohamed-traore-2ekkp/people-detection-general
+* https://universe.roboflow.com/labeler-projects/construction-madness/

README.md

@@ -4,7 +4,19 @@ task_categories:
 tags:
 - roboflow
 - roboflow2huggingface
-
+- Construction
+- Logistics
+- Utilities
+- Damage Risk
+- Ppe
+- Construction
+- Utilities
+- Manufacturing
+- Logistics
+- Ppe
+- Assembly Line
+- Warehouse
+- Factory
 ---
 
 <div align="center">
@@ -14,14 +26,14 @@ tags:
 ### Dataset Labels
 
 ```
-['planes']
+['barricade', 'dumpster', 'excavators', 'gloves', 'hardhat', 'mask', 'no-hardhat', 'no-mask', 'no-safety vest', 'person', 'safety net', 'safety shoes', 'safety vest', 'dump truck', 'mini-van', 'truck', 'wheel loader']
 ```
 
 
 ### Number of Images
 
 ```json
-{'test': 25, 'train': 175, 'valid': 50}
+{'valid': 57, 'train': 307, 'test': 34}
 ```
 
 
@@ -43,20 +55,20 @@ example = ds['train'][0]
 ```
 
 ### Roboflow Dataset Page
-[https://universe.roboflow.com/skybot-cam/overhead-plane-detector/dataset/4](https://universe.roboflow.com/skybot-cam/overhead-plane-detector/dataset/4?ref=roboflow2huggingface)
+[https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety/dataset/1](https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety/dataset/1?ref=roboflow2huggingface)
 
 ### Citation
 
 ```
-@misc{ overhead-plane-detector_dataset,
-    title = { Overhead Plane Detector Dataset },
+@misc{ construction-site-safety_dataset,
+    title = { Construction Site Safety Dataset },
     type = { Open Source Dataset },
-    author = { SkyBot Cam },
-    howpublished = { \\url{ https://universe.roboflow.com/skybot-cam/overhead-plane-detector } },
-    url = { https://universe.roboflow.com/skybot-cam/overhead-plane-detector },
+    author = { Roboflow Universe Projects },
+    howpublished = { \\url{ https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety } },
+    url = { https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety },
     journal = { Roboflow Universe },
     publisher = { Roboflow },
-    year = { 2022 },
+    year = { 2023 },
     month = { jan },
     note = { visited on 2023-01-18 },
 }
@@ -66,12 +78,21 @@ example = ds['train'][0]
 CC BY 4.0
 
 ### Dataset Summary
-This dataset was exported via roboflow.ai on March 30, 2022 at 3:11 PM GMT
+This dataset was exported via roboflow.com on December 29, 2022 at 11:22 AM 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 unstructured image data
+* annotate, and create datasets
+* export, train, and deploy computer vision models
+* use active learning to improve your dataset over time
 
-It includes 250 images.
-Planes are annotated in COCO format.
+It includes 398 images.
+Construction are annotated in COCO format.
 
 The following pre-processing was applied to each image:
+* Auto-orientation of pixel data (with EXIF-orientation stripping)
 
 No image augmentation techniques were applied.
 

README.roboflow.txt

@@ -1,13 +1,22 @@
 
-Overhead Plane Detector - v4 raw images
+Construction Site Safety - v1 original_raw-images
 ==============================
 
-This dataset was exported via roboflow.ai on March 30, 2022 at 3:11 PM GMT
+This dataset was exported via roboflow.com on December 29, 2022 at 11:22 AM GMT
 
-It includes 250 images.
-Planes are annotated in COCO format.
+Roboflow is an end-to-end computer vision platform that helps you
+* collaborate with your team on computer vision projects
+* collect & organize images
+* understand unstructured image data
+* annotate, and create datasets
+* export, train, and deploy computer vision models
+* use active learning to improve your dataset over time
+
+It includes 398 images.
+Construction are annotated in COCO format.
 
 The following pre-processing was applied to each image:
+* Auto-orientation of pixel data (with EXIF-orientation stripping)
 
 No image augmentation techniques were applied.
 

data/test.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3aa0da3e86753e6a47b12ba3efd39ab9135bbe156bc4eca3bd42b92f395fa5ad
-size 1885664
+oid sha256:08fba642491dd486df861c055ea7bff74142ac126a1ff1dc45e4819802e3e4b8
+size 1796467

data/train.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cea2a044e36e323496eae1b73941d927d8c6bea2af21213360d93bb96b6f7904
-size 14475473
+oid sha256:26bc101596c1933dac85de617c12fb1839ac4fbc0c894f42dc4ebaeac333461f
+size 22259647

data/valid-mini.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c29307d0eae74e556fd15fe720bf422ee694040de48241f18a61d59040580620
-size 143207
+oid sha256:1356199c763408c99a842b9beda048d7fcc488fd6033045eb1cd2b498652b601
+size 97565

data/valid.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d4c59404660d6df33f083d674897e90288932989b33d38de6d71680fa172c43c
-size 3939295
+oid sha256:32d5e6f68ada7bbf6c8304465f283e78c93fe783f8e765e3326ba84f6c98cabd
+size 3338795

plane-detection.py

@@ -5,23 +5,23 @@ import os
 import datasets
 
 
-_HOMEPAGE = "https://universe.roboflow.com/skybot-cam/overhead-plane-detector/dataset/4"
+_HOMEPAGE = "https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety/dataset/1"
 _LICENSE = "CC BY 4.0"
 _CITATION = """\
-@misc{ overhead-plane-detector_dataset,
-    title = { Overhead Plane Detector Dataset },
+@misc{ construction-site-safety_dataset,
+    title = { Construction Site Safety Dataset },
     type = { Open Source Dataset },
-    author = { SkyBot Cam },
-    howpublished = { \\url{ https://universe.roboflow.com/skybot-cam/overhead-plane-detector } },
-    url = { https://universe.roboflow.com/skybot-cam/overhead-plane-detector },
+    author = { Roboflow Universe Projects },
+    howpublished = { \\url{ https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety } },
+    url = { https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety },
     journal = { Roboflow Universe },
     publisher = { Roboflow },
-    year = { 2022 },
+    year = { 2023 },
     month = { jan },
     note = { visited on 2023-01-18 },
 }
 """
-_CATEGORIES = ['planes']
+_CATEGORIES = ['barricade', 'dumpster', 'excavators', 'gloves', 'hardhat', 'mask', 'no-hardhat', 'no-mask', 'no-safety vest', 'person', 'safety net', 'safety shoes', 'safety vest', 'dump truck', 'mini-van', 'truck', 'wheel loader']
 _ANNOTATION_FILENAME = "_annotations.coco.json"
 
 

split_name_to_num_samples.json

@@ -1 +1 @@
-{"test": 25, "train": 175, "valid": 50}
+{"valid": 57, "train": 307, "test": 34}