2022_新竹市交通影像資料_含點中心標註_18000圖_160000點

Hsinchu city traffic image data_with point center annotation

Dataset Description

• This data set is a fisheye lens video file of important intersections in Hsinchu City, provided by Hsinchu City Police Department. Original video reference:

  • (This video is from the fish-eye sample) https://youtu.be/S-tYTAaQgIs

• Contains traffic data sets of four intersections in Hsinchu City, including about 18000 images and about 160000 point annotations

  • Use the point center labeling method,
  • Only objects within the ROI range are marked
  • The content of the label is divided into: large car, small car, locomotive
  • Sample file is here including 1 road and 326 frames download here

• It can be used for AI scientific research and development, everyone is welcome to apply.

Data information

• This information is provided by Hsinchu City Police Department
• Marked by Ruoshui Technology
• And the data service is provided by the State Grid Center

video date

• Feb, 2022

file description

• FishlenTraffic_R3p1_Center_7696f58307p.zip
  • 7696 frames, 58307 points, 19GB
  • road id : R01 ~ R25

• FishlenTraffic_R3p2_Center_10398f101704p.zip

  • 10398 frames，101704 points, 33GB
  • road id : R26~R61

• This data set contains two compressed files. After decompression, the folders represent each intersection.

Each compressed file contains an array of png images, json annotation files, and bound annotation images. The following examples illustrate:

• 01_roi.txt => mark the roi range
• frame_00000.png => original image
• frame_00000.json => annotation file

• simulation/frame_00000_out.png => Binding annotated image

• Figure 1: The marked frame_00000.png, red dots are locomotives, green dots are small cars, blue dots are large cars, the ROI range is near the intersection area within the zebra crossing, please refer to the roi.txt of each intersection for details

• Figure 2: roi.txt two points are combined into a line, there are multiple lines at one intersection

  • line : [ [x1,y1], [x2,y2] ]

• Figure 3: Mark json file reference

Demonstration application

• ai automatic labeling application (this video is the former fisheye of Hsinchu Industrial Research Institute, using AI model to automatically determine 2021/09/27) https://youtu.be/sjUQ-Ayxxtk

資料集說明

• 此資料集為新竹市重要路口的魚眼鏡頭影片檔，由新竹市警察局提供。原始影片參考：https://youtu.be/S-tYTAaQgIs

• 內含多新竹市路口的交通資料集，含約 1萬8千張影像與約16萬個點標註

  • 使用 點中心 標註方式，
  • 在ROI範圍內的物件才標註
  • 標註內容分為: 大型車、小型車、機車
  • 參考檔為一路段 652張圖，自由下載 download here

• 可用於AI科學研發，歡迎大家申請使用。

資料資訊

• 此資料由新竹市警察局提供
• 由若水科技標註
• 並由國網中心提供資料服務

影片日期

• 2022 年 2 月

檔案說明

• FishlenTraffic_R3p1_Center_7696f58307p.zip
  • 含 7696 圖，58307點標註，19GB
  • R01 ~ R25
• FishlenTraffic_R3p2_Center_10398f101704p.zip
  • 含 10398 圖，101704點標註，33GB
  • R26~R61

每個壓縮檔內包含數組 png影像、json標註檔、綁定標註的影像。 以下舉例說明:

R01 => 路段編號 01_roi.txt => 標註 roi 範圍 frame_00000.png => 原始影像 frame_00000.json => 標註檔 simulation/frame_00000_out.png => 綁定標註的影像

• 圖一：經標註的frame_00000.png，紅點為機車，綠點為小型車，藍點為大型車，ROI範圍在斑馬線內的十字路口區附近，詳細參考各路口的 roi.txt

• 圖二：roi.txt 兩點組合成一條線，一個路口有多條線

  • line : [ [x1,y1], [x2,y2] ]

• 圖三 : 標註json file 參考

示範應用

• ai 自動標註應用 (此段影片為 新竹工研院前魚眼，使用AI模型自動判定 2021/09/27) https://youtu.be/sjUQ-Ayxxtk

路口對應表(編號,路口名稱,時間)

• R01 ,中正路與北大路口,2022_02_24_8上午_00_04
• R02 ,經國路與中正路口,2022_02_24_8上午_08_35
• R03 ,中正路419巷與中正路,2022_02_24_12下午_09_41
• R04 ,中正路與境福街口,2022_02_24_12下午_38_30
• R05 ,中華路五段160巷口,2022_02_08_12下午_18_19
• R06 ,中山路與中華路三段路口,2022_02_16_7上午_35_32
• R07 ,中華路四段與東華路口,2022_02_16_7上午_16_31
• R08 ,中華路四段與牛埔南路口_南端,2022_02_10_8上午_04_18
• R09 ,中華路五段552巷口,2022_02_18_5下午_29_37
• R10 ,中華路二段495號停車場前,2022_02_16_7上午_51_35
• R11 ,公道三路與竹香南北路口,2022_02_14_5下午_43_35
• R12 ,牛埔路與公道三路口,2022_02_14_5下午_43_35
• R13 ,48光復路與大學路口,2022_02_25_11上午_53_54
• R14 ,光復路與建新路口,2022_02_24_5下午_50_46
• R15 ,天府路與延平路口,2022_02_17_8上午_38_14
• R16 ,延平路二段與香雅橋口,2022_02_17_12下午_29_41
• R17 ,東大路與南大路口,2022_02_16_12下午_19_52
• R18 ,經國路與東大路口,2022_02_16_12下午_19_52
• R19 ,東大路與鐵道路口,2022_02_16_12下午_19_52
• R20 ,東大路與天府路口,2022_02_24_7上午_39_51
• R21 ,東大路與西濱路口,2022_02_16_12下午_19_52
• R22 ,中華路與經國路口_北端,2022_02_15_8上午_09_39
• R23 ,經國路與中正路口,2022_02_24_12下午_24_24
• R24 ,公道五慈雲路口,2022_02_24_5下午_45_54
• R25 ,慈雲路與埔頂路口,2022_02_24_5下午_28_56
• R26 ,中華路與經國路口,2022_02_24_12下午_24_24
• R27 ,中華路與經國路口,2022_02_24_5下午_43_15
• R28 ,中華路與經國路口,2022_02_25_7上午_19_52
• R29 ,中華路與經國路口,2022_02_25_7上午_49_24
• R30 ,東大路與南大路口,2022_02_15_8上午_14_45
• R31 ,公道五慈雲路口,2022_02_24_8上午_19_52
• R32 ,慈雲路與埔頂路口,2022_02_21_12下午_13_56
• R33 ,慈雲路與埔頂路口,2022_02_24_5下午_45_54
• R34 ,復路與建新路口,2022_02_24_12下午_21_45
• R35 ,復路與建新路口,2022_02_24_5下午_28_25
• R36 ,復路與建新路口,2022_02_25_12下午_30_01
• R37 ,復路與建新路口,2022_02_25_6上午_59_58
• R38 ,復路與建新路口,2022_02_25_8上午_10_42
• R39 ,經國路與中正路口,2022_02_24_12下午_24_24
• R40 ,經國路與中正路口,2022_02_24_5下午_43_15
• R41 ,經國路與中正路口,2022_02_24_7上午_50_11
• R42 ,經國路與西大路口,2022_02_15_8上午_09_39
• R43 ,經國路與西大路口,2022_02_24_12下午_24_24
• R44 ,東大路與鐵道路口,2022_02_16_5下午_39_27
• R45 ,東大路與鐵道路口,2022_02_24_7上午_39_51
• R46 ,東大路與天府路口,2022_02_15_8上午_14_45
• R47 ,經國路與民生路口,2022_02_24_5下午_43_15
• R48 ,經國路與民生路口,2022_02_25_7上午_19_52
• R49 ,經國路與民生路口,2022_02_25_7上午_49_24
• R50 ,中華路四段與經國路口,2022_02_24_12下午_24_24
• R51 ,天府路與延平路口,2022_02_15_5下午_39_54
• R52 ,天府路與延平路口,2022_02_25_7上午_45_01
• R53 ,經國路與和平路口,2022_02_24_12下午_24_24
• R54 ,經國路與和平路口,2022_02_24_12下午_24_24(1)
• R55 ,經國路與和平路口,2022_02_24_5下午_43_15
• R56 ,中正路與境福街口,2022_02_18_5下午_09_46
• R57 ,東大路與西濱路口,2022_02_15_8上午_14_45
• R58 ,東大路與西濱路口,2022_02_16_5下午_39_27
• R59 ,經國路與磐石路口,2022_02_24_5下午_43_15
• R60 ,經國路與磐石路口,2022_02_25_7上午_19_52
• R61 ,延平路二段與香雅橋口,2022_02_15_5下午_39_54