Top Source Datasets and Models
The datasets below can be used to train fine-tuned models for source detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
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Object Detection
400 images
* Random brigthness adjustment of between -6 and +6 percent* annotate, and create datasets* collaborate with your team on computer vision projects* use active learning to improve your dataset over time28347Roboflow is an end-to-end computer vision platform that helps youThe following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:krx
Object Detection
8.22k images
number* Random rotation of between -2 and +2 degrees* Random shear of between -10° to +10° horizontally and -10° to +10° vertically* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time01100101102103104105106107108
![[V1] CareTech Combined Dataset project thumbnail](https://source.roboflow.com/h8YCgQ4SlYbJQN06SbRNpgs9VyX2/y6sJQXthEsWsjA79dClB/thumb.jpg)
Object Detection
40 images·2 models·7
"capacitor jumper" CJ1"capacitor jumper" CJ2"component text" " CC BE 10000000""component text" "-309 LL6""component text" "0 1 2 3 4 5 6 7""component text" "0 N""component text" "0001 5293 170A""component text" "0123456789ABCDEF""component text" "021 LDBM N389""component text" "0821-1X1T-43-F 1402 WM""component text" "0833 LTC2274 UJ BT267910""component text" "085811 B4T EHCR""component text" "1 2 3 4 5 6 7 8""component text" "1 2 3 4""component text" "1 2 3""component text" "1 2""component text" "100 25V UT""component text" "100 50V UT""component text" "100 6V""component text" "100 CFK 7BD"
Object Detection
6.86k images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Random rotation of between -10 and +10 degrees- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time==============================Orientation 9 models - v4 2025-01-30 12:08pmRoboflow is an end-to-end computer vision platform that helps youThe dataset includes 6890 images-The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:The following transformations were applied to the bounding boxes of each image:Unknown-mRm4 are annotated in YOLOv8 Oriented Object Detection format-visit https:--github-com-roboflow-notebooks
Object Detection
3.28k images·1
* Auto-orientation of pixel data (with EXIF-orientation stripping)* Randomly crop between 0 and 20 percent of the image* Resize to 640x640 (Stretch)==============================It includes 3328 images.Liqours are annotated in YOLO v5 PyTorch format.The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:This dataset was exported via roboflow.ai on May 23, 2022 at 5:15 PM GMTamarettocamparicointreauginkahlualiquors - v2 datasetv2rumscotch-whiskysweet-vermouthtequilavodka
Object Detection
9.47k images·1 model·18
Object Detection
40 images·2
"capacitor jumper" CJ1"capacitor jumper" CJ2"component text" " CC BE 10000000""component text" "-309 LL6""component text" "0 1 2 3 4 5 6 7""component text" "0 N""component text" "0001 5293 170A""component text" "0123456789ABCDEF""component text" "021 LDBM N389""component text" "0821-1X1T-43-F 1402 WM""component text" "0833 LTC2274 UJ BT267910""component text" "085811 B4T EHCR""component text" "1 2 3 4 5 6 7 8""component text" "1 2 3 4""component text" "1 2 3""component text" "1 2""component text" "100 25V UT""component text" "100 50V UT""component text" "100 6V""component text" "100 CFK 7BD"
Object Detection
40 images·12
"capacitor jumper" CJ1"capacitor jumper" CJ2"component text" " CC BE 10000000""component text" "-309 LL6""component text" "0 1 2 3 4 5 6 7""component text" "0 N""component text" "0001 5293 170A""component text" "0123456789ABCDEF""component text" "021 LDBM N389""component text" "0821-1X1T-43-F 1402 WM""component text" "0833 LTC2274 UJ BT267910""component text" "085811 B4T EHCR""component text" "1 2 3 4 5 6 7 8""component text" "1 2 3 4""component text" "1 2 3""component text" "1 2""component text" "100 25V UT""component text" "100 50V UT""component text" "100 6V""component text" "100 CFK 7BD"
Object Detection
43 images·2
"capacitor jumper" CJ1"capacitor jumper" CJ2"component text" "-309 LL6""component text" "0 N""component text" "0001 5293 170A""component text" "021 LDBM N389""component text" "0833 LTC2274 UJ BT267910""component text" "085811 B4T EHCR""component text" "0N 5C""component text" "1 2 3 4""component text" "1 2""component text" "100 CFK 7BD""component text" "100 CFK- 7BD""component text" "100 VFK- 87""component text" "100 VFK- 8R7""component text" "106C 43JJ2""component text" "107A 938H4""component text" "12-000""component text" "15 203""component text" "150 CFK- 0C7"
Object Detection
43 images·4
"capacitor jumper" CJ1"capacitor jumper" CJ2"component text" "-309 LL6""component text" "0 N""component text" "0001 5293 170A""component text" "021 LDBM N389""component text" "0821-1X1T-43-F 1402 WM""component text" "0833 LTC2274 UJ BT267910""component text" "085811 B4T EHCR""component text" "0N 5C""component text" "1 2 3 4""component text" "1 2""component text" "100 CFK 7BD""component text" "100 CFK- 7BD""component text" "100 VFK- 87""component text" "100 VFK- 8R7""component text" "106C 43JJ2""component text" "107A 938H4""component text" "12-000""component text" "15 203"
Object Detection
41 images·4
"component text" "1 2""component text" "16 105""component text" "2 G""component text" "233 834DA""component text" "25R03213 E400222A""component text" "3 J""component text" "47 25S- T85""component text" "93AA66CI SN 1103 DE0""component text" "ALTERA Cyclone V 5CEBA4F23C8N F BABAU1337A TAIWAN NABAU303016 301FA3T0A""component text" "ALTERA Cyclone V 5CEBA4U15C8N F CABAU1337A KOREA NABAU303013 301FA3DOB""component text" "DAV88 808V0""component text" "EN5322 E020MC H337""component text" "EN5322 E02BSC""component text" "EN5336QI E02CN U330""component text" "EPCQ32M Q245A""component text" "FCC ID: NKRM14A2A Made In China""component text" "FTDI 1238-C D6LNL-1 FT2232HL""component text" "MCC 5K22""component text" "MR2A1BAMA35 UCTCT8R13198""component text" "O N"
Object Detection
1.61k images·1 model·3
object* 50% probability of horizontal flip* Resize to 640x640 (Stretch)* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time==============================Animal detect - v2 2023-04-25 3:38pmAnimals are annotated in YOLOv8 format.For state of the art Computer Vision training notebooks you can use with this dataset,Person dataset - v3 2023-11-16 1:52amRoboflow is an end-to-end computer vision platform that helps youThe dataset includes 269 images.The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:This dataset was exported via roboflow.com on April 25, 2023 at 10:09 AM GMTTo find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
Object Detection
2.45k images·1 model
object* 50% probability of horizontal flip* Auto-orientation of pixel data (with EXIF-orientation stripping)* Resize to 640x640 (Stretch)* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time20==============================For state of the art Computer Vision training notebooks you can use with this dataset,Roboflow is an end-to-end computer vision platform that helps youSignals are annotated in YOLO v5 PyTorch format.The dataset includes 2587 images.The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:This dataset was exported via roboflow.com on November 25, 2023 at 12:38 AM GMTTo find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
Object Detection
2k images·1 model
AgeConcomitant Drugs and Dates of AdministrationCountryDOBDaily DoseDate Received by ManufacturerDate of this ReportDid Reaction AbateDid Reaction ReappearIndication For UseInitialsMFR Control NumberName and Address of ReporterName and Addresss of ManufacturerOther Relevant HistoryReaction OnsetReactionsRemarksReport SourceReport Type
Object Detection
806 images·1 model
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Random Gaussian blur of between 0 and 2-5 pixels- Random rotation of between -20 and +20 degrees- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time100101102103104105106107108109110111112
Object Detection
1.43k images·1 model
-- 50- probability of horizontal flip- Auto-orientation of pixel data -with EXIF-orientation stripping-- Grayscale -CRT phosphor-- Random Gaussian blur of between 0 and 2-5 pixels- Randomly crop between 0 and 20 percent of the image- annotate- and create datasets- collaborate with your team on computer vision projects- collect - organize images- export- train- and deploy computer vision models- understand and search unstructured image data- use active learning to improve your dataset over time2324262728293031
Object Detection
7.11k images
-- Auto-orientation of pixel data (with EXIF-orientation stripping)- Random rotation of between -10 and +10 degrees- Random shear of between -14° to +14° horizontally and -9° to +9° vertically- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time==============================IrgaMushrooms are annotated in YOLOv8 format-Roboflow is an end-to-end computer vision platform that helps youThe dataset includes 11376 images-The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:boyroshnikfizaliskastenikapaslentern
Classification
5.36k images·2
* Random rotation of between -15 and +15 degrees* Random shear of between -15° to +15° horizontally and -15° to +15° vertically* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time192021222324252627282930
Object Detection
1.44k images·1 model·5
* Auto-orientation of pixel data (with EXIF-orientation stripping)* Resize to 640x640 (Stretch)* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time192021222324252627282930
Classification
9.56k images·2
* 50% probability of horizontal flip* 50% probability of vertical flip* Auto-orientation of pixel data (with EXIF-orientation stripping)* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down* Random Gaussian blur of between 0 and 1.75 pixels* Random brigthness adjustment of between -25 and +25 percent* Random exposure adjustment of between -15 and +15 percent* Random rotation of between -10 and +10 degrees* Random shear of between -2° to +2° horizontally and -2° to +2° vertically* Randomly crop between 0 and 15 percent of the image* Resize to 640x640 (Stretch)* Salt and pepper noise was applied to 2 percent of pixels* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time2930
Object Detection
113 images
Object Detection
2.11k images·1 model
* Auto-orientation of pixel data (with EXIF-orientation stripping)* Random rotation of between -15 and +15 degrees* Resize to 640x640 (Fit within)* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time==============================For state of the art Computer Vision training notebooks you can use with this dataset,LAP Detection - v5 2024-08-22 3:25pmLAP-number are annotated in YOLOv8 format.Roboflow is an end-to-end computer vision platform that helps youThe dataset includes 6073 images.The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:This dataset was exported via roboflow.com on August 22, 2024 at 4:18 PM GMTTo find over 100k other datasets and pre-trained models, visit https://universe.roboflow.comvisit https://github.com/roboflow/notebooks
Object Detection
40 images·4 models·3
"capacitor jumper" CJ1"capacitor jumper" CJ2"component text" " CC BE 10000000""component text" "-309 LL6""component text" "0 1 2 3 4 5 6 7""component text" "0 N""component text" "0001 5293 170A""component text" "0123456789ABCDEF""component text" "021 LDBM N389""component text" "0821-1X1T-43-F 1402 WM""component text" "0833 LTC2274 UJ BT267910""component text" "085811 B4T EHCR""component text" "1 2 3 4 5 6 7 8""component text" "1 2 3 4""component text" "1 2 3""component text" "1 2""component text" "100 6V""component text" "100 CFK 7BD""component text" "100 CFK- 7BD""component text" "100 VFK- 87"
Object Detection
3.26k images·2
* Auto-contrast via contrast stretching* Auto-orientation of pixel data (with EXIF-orientation stripping)* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down* Random shear of between -14° to +14° horizontally and -15° to +15° vertically* Resize to 800x800 (Stretch)* Salt and pepper noise was applied to 1.13 percent of pixels* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time100101102103104105106107
Object Detection
1.76k images
* 50% probability of horizontal flip* 50% probability of vertical flip* Auto-orientation of pixel data (with EXIF-orientation stripping)* Random Gaussian blur of between 0 and 1.5 pixels* Random exposure adjustment of between -10 and +10 percent* Randomly crop between 0 and 20 percent of the image* Resize to 640x640 (Stretch)* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand and search unstructured image data* use active learning to improve your dataset over time242526==============================American Sign Language Letters - v2 2024-12-10 12:43pmFor state of the art Computer Vision training notebooks you can use with this dataset,Letters are annotated in YOLOv8 format.
Classification
1.72k images·3
* 50% probability of horizontal flip* Auto-orientation of pixel data (with EXIF-orientation stripping)* Random Gaussian blur of between 0 and 1.25 pixels* Random brigthness adjustment of between -25 and +25 percent* Random rotation of between -5 and +5 degrees* Random shear of between -5° to +5° horizontally and -5° to +5° vertically* Randomly crop between 0 and 20 percent of the image* Resize to 416x416 (Stretch)* annotate, and create datasets* collaborate with your team on computer vision projects* collect & organize images* export, train, and deploy computer vision models* understand unstructured image data* use active learning to improve your dataset over time22232425==============================American Sign Language Letters - v1 v1
Object Detection
3.58k images·1 model
Object Detection
35 images·2
"component text" "47 25S- T85""component text" "697 6K 206""component text" "93AA66CI SN 1103 DE0""component text" "MAXIM MAX2837 ETM 509 8SY03AK""component text" "MAXIM MAX5864 ETM 405 BQGT1AA""component text" "MCC 5K22""component text" "MXU 58810""component text" "NXP LPC4320FBD144 SC3N9 04 9SD15070C""component text" "RJ9 117-5""component text" "S15351 BMF020 1452""component text" "T250 VU4T""component text" "XILINX XC2C64A VQG100AMS1201 F4339159A 7C""component text" 102"component text" 103"component text" 220"component text" 472"component text" 505Y"diode zener array" DA1"diode zener array" DA3"electrolytic capacitor" C157
Object Detection
3.79k images·3 models
deerpersonraccoon* Auto-contrast via histogram equalization* Auto-orientation of pixel data (with EXIF-orientation stripping)* Random Gaussian blur of between 0 and 2 pixels* Random brigthness adjustment of between -50 and 0 percent* Resize to 640x640 (Stretch)* annotate, and create datasets* collect & organize images* export, train, and deploy computer vision models* use active learning to improve your dataset over time0==============================DeerFor state of the art Computer Vision training notebooks you can use with this dataset,Roe deerThe dataset includes 734 images.The following augmentation was applied to create 3 versions of each source image:The following pre-processing was applied to each image:
Object Detection
16.5k images·1 model
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Grayscale (CRT phosphor)- Random Gaussian blur of between 0 and 2-5 pixels- Random brigthness adjustment of between -35 and +35 percent- Random rotation of between -25 and +25 degrees- Randomly crop between 0 and 25 percent of the image- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time26272829303132333435
Object Detection
10.2k images
- Auto-orientation of pixel data (with EXIF-orientation stripping)- Random rotation of between -15 and +15 degrees- Resize to 640x640 (Stretch)- collaborate with your team on computer vision projects- understand and search unstructured image data- use active learning to improve your dataset over time2223242526272829303132333435