Top Folder Datasets and Models
The datasets below can be used to train fine-tuned models for folder detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
Instance Segmentation
2.89k images
Object Detection
383 images·1
Object Detection
1.28k images·2 models
Classification
9.98k images·2
fanpenwaterAD calcium milk Nescafe Snickers Xiaoxiaosu dish soapAD calcium milk Oreo XiaoxiaosuAD calcium milk Oreo Xiaoxiaosu paper napkinAD calcium milk Oreo dish soap paper napkinAD calcium milk SnickersAD calcium milk Snickers toilet waterAD calcium milk dish soap paper napkinAD calcium milk toilet waterChestnut rice strip Leshi potato chips Prawn Crackers Snickers folder pen water water glassChestnut rice strip Leshi potato chips Prawn Crackers Snickers folder water water glassChestnut rice strip Leshi potato chips Prawn Crackers penChestnut rice strip Leshi potato chips penChestnut rice strip Prawn CrackersChestnut rice strip Prawn Crackers ShaQima pen water water glassChestnut rice strip Prawn Crackers ShaQima water water glassChestnut rice strip paper napkinChestnut rice strip paper napkin pen
Classification
310 images
<?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Afghan_11172-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>386<-width> <height>500<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Afghan_hound<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>77<-xmin> <ymin>190<-ymin> <xmax>370<-xmax> <ymax>433<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Afghan_3531-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>383<-width> <height>500<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Afghan_hound<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>205<-xmin> <ymin>71<-ymin> <xmax>331<-xmax> <ymax>411<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Afghan_357-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>368<-width> <height>500<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Afghan_hound<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>96<-xmin> <ymin>82<-ymin> <xmax>280<-xmax> <ymax>476<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Afghan_5559-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>342<-width> <height>500<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Afghan_hound<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>103<-xmin> <ymin>211<-ymin> <xmax>301<-xmax> <ymax>423<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>African_2192-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>333<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>African_hunting_dog<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>1<-xmin> <ymin>11<-ymin> <xmax>499<-xmax> <ymax>331<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>African_2435-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>350<-width> <height>250<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>African_hunting_dog<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>0<-xmin> <ymin>28<-ymin> <xmax>320<-xmax> <ymax>227<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>African_5683-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>333<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>African_hunting_dog<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>144<-xmin> <ymin>58<-ymin> <xmax>362<-xmax> <ymax>314<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>African_8037-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>333<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>African_hunting_dog<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>100<-xmin> <ymin>6<-ymin> <xmax>450<-xmax> <ymax>332<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Airedale_1736-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>200<-width> <height>226<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Airedale<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>34<-xmin> <ymin>1<-ymin> <xmax>188<-xmax> <ymax>206<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Airedale_3500-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>300<-width> <height>250<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Airedale<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>10<-xmin> <ymin>21<-ymin> <xmax>272<-xmax> <ymax>239<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Airedale_3879-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>358<-width> <height>500<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Airedale<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>45<-xmin> <ymin>27<-ymin> <xmax>321<-xmax> <ymax>491<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Airedale_5048-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>369<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Airedale<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>14<-xmin> <ymin>103<-ymin> <xmax>424<-xmax> <ymax>357<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Airedale_7790-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>334<-width> <height>500<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Airedale<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>28<-xmin> <ymin>133<-ymin> <xmax>332<-xmax> <ymax>498<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Airedale_8826-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>375<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Airedale<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>75<-xmin> <ymin>112<-ymin> <xmax>416<-xmax> <ymax>250<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>American_9797-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>414<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>American_Staffordshire_terrier<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>6<-xmin> <ymin>47<-ymin> <xmax>498<-xmax> <ymax>412<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Appenzeller_2666-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>375<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Appenzeller<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>0<-xmin> <ymin>45<-ymin> <xmax>372<-xmax> <ymax>374<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Appenzeller_2913-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>333<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Appenzeller<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>72<-xmin> <ymin>16<-ymin> <xmax>402<-xmax> <ymax>287<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Appenzeller_3971-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>500<-width> <height>335<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Appenzeller<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>142<-xmin> <ymin>45<-ymin> <xmax>499<-xmax> <ymax>276<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Appenzeller_7392-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>400<-width> <height>481<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Appenzeller<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>115<-xmin> <ymin>38<-ymin> <xmax>344<-xmax> <ymax>429<-ymax> <-bndbox> <-object> <-annotation><?xml version=1-0 encoding=utf-8?> <annotation> <folder -> <filename>Australian_1536-jpg<-filename> <source> <database>ImageNet database<-database> <-source> <size> <width>200<-width> <height>194<-height> <depth>3<-depth> <-size> <segment>0<-segment> <object> <name>Australian_terrier<-name> <pose>Unspecified<-pose> <truncated>0<-truncated> <difficult>0<-difficult> <bndbox> <xmin>0<-xmin> <ymin>5<-ymin> <xmax>199<-xmax> <ymax>193<-ymax> <-bndbox> <-object> <-annotation>
Classification
144 images
Object Detection
4k images·1 model·19
bedcabinetmirrormobilesofaA black desk lamp on top of a desk next to white sheets of paper and a science posterA black laptop, a black computer screen, a gray and black keyboard and a computer mouse on top of a black desk and chairA black laptop, a black computer screen, a gray and black keyboard and a computer mouse on top of a deskA black laptop, a gray and black keyboard and a computer mouse on top of a white piece of paper on a deskA black laptop, some cables, a black computer screen on top of a deskA black stapler, some glasses and a black cable on a deskA blue and yellow can on top of a desk next to some white sheets of paper, a computer screen and a keyboardA blue chair and a black floorA blue vending machineA bottle of water on top of a desk next to a black chairA cabinet of foldersA cabinet of folders and a chairA cabinet of folders and a window with curtainsA cabinet of folders and some posters fixed on the wallA cabinet of folders and some white sheets and some chairs
Classification
9.98k images·1
fanpenwaterAD calcium milk Nescafe Snickers Xiaoxiaosu dish soapAD calcium milk Oreo XiaoxiaosuAD calcium milk Oreo Xiaoxiaosu paper napkinAD calcium milk Oreo dish soap paper napkinAD calcium milk SnickersAD calcium milk Snickers toilet waterAD calcium milk dish soap paper napkinAD calcium milk toilet waterChestnut rice strip Leshi potato chips Prawn Crackers Snickers folder pen water water glassChestnut rice strip Leshi potato chips Prawn Crackers Snickers folder water water glassChestnut rice strip Leshi potato chips Prawn Crackers penChestnut rice strip Leshi potato chips penChestnut rice strip Prawn CrackersChestnut rice strip Prawn Crackers ShaQima pen water water glassChestnut rice strip Prawn Crackers ShaQima water water glassChestnut rice strip paper napkinChestnut rice strip paper napkin pen
Object Detection
8.95k images·1 model·63
Classification
10k images·1
fanpenwaterAD calcium milk Nescafe Snickers Xiaoxiaosu dish soapAD calcium milk Oreo XiaoxiaosuAD calcium milk Oreo Xiaoxiaosu paper napkinAD calcium milk Oreo dish soap paper napkinAD calcium milk SnickersAD calcium milk Snickers toilet waterAD calcium milk dish soap paper napkinAD calcium milk toilet waterChestnut rice strip Leshi potato chips Prawn Crackers Snickers folder pen water water glassChestnut rice strip Leshi potato chips Prawn Crackers Snickers folder water water glassChestnut rice strip Leshi potato chips Prawn Crackers penChestnut rice strip Leshi potato chips penChestnut rice strip Prawn CrackersChestnut rice strip Prawn Crackers ShaQima pen water water glassChestnut rice strip Prawn Crackers ShaQima water water glassChestnut rice strip paper napkinChestnut rice strip paper napkin pen
Classification
5k images·1 model
'mongst nonemigrant ecclesia9th sergelim DelaplaineA&P Hordville siliconsAA mesmerism chorioadenomaACWP hypohepatia hedginglyAIDS off-bitten retroactivelyASTMS brewst rehumiliatedATP2 flagellations green-fishAbercrombie jemidars choristerAbruzzi forehock LampsilisAcacea quatral enhancersAcalypterae eyewinker DominoAcanthodes calyceal tubectomyAcanthodidae elastics paleoanthropologyAcolhua Hammondsport guttulateAdapis PIO LyssaAdel endover chequeredAdventism discanonized hayliftAeria braveries coelomicAfridi whoosh mycol
