[{"data":1,"prerenderedAt":226},["ShallowReactive",2],{"project-15582714":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":10,"maker":11,"posted_at":12,"year":13,"points":14,"comments":15,"rank_in_year":16,"shown_in_year":17,"top":18,"tier":19,"category":20,"subcategory":21,"format":22,"keywords":23,"reception":28,"sentiment":29,"stance_mix":30,"scored_comments":35,"aspects":36,"strip":42,"post_text":44,"what":45,"said":61,"maker_in_thread":123,"shape":125,"grid":130,"attempts":188,"same_week":189,"maker_shows":38,"maker_hidden":218,"reader_version":219,"card":220},"15582714","Vehicle Detection","using machine learning and computer vision","title","Show HN: Vehicle Detection – using machine learning and computer vision","https:\u002F\u002Fgithub.com\u002Ftatsuyah\u002Fvehicle-detection","github.com","tsy",1509329882,2017,153,21,246,2242,11,"notable","ai","computer vision","library",[24,21,25,26,27],"vehicle detection","machine learning","hog svm","opencv","mixed",0.181,{"positive":31,"neutral":32,"mixed":33,"critical":34},5,6,0,2,13,{"execution":37,"idea":39,"performance":40,"docs":41},{"positive":38,"critical":38},1,{"positive":34,"critical":33},{"positive":33,"critical":38},{"positive":38,"critical":33},[43,31,33,33,31,43,33,33,33,33,33,31,38,33,31,31,43,43,43,38,43],3,null,{"problem":46,"audience":44,"pricing":44,"motivation":44,"time_to_build":44,"stack":52,"openness":60,"stage":60,"team_size":60},{"value":47,"source":48,"evidence":49},"Detecting vehicles in images","inferred",[50],{"id":51},"post",[53],{"value":54,"source":48,"evidence":55},"HOG + SVM",[56],{"id":57,"by":58,"text":59},"15583645","edshiro","Good work! I did this project as well about a week ago. I will shamelessly also share my writings on this project:…","unknown",{"praise":62,"objections":72,"requests":88,"questions":100,"alternatives":108},[63],{"value":64,"source":65,"evidence":66},"Good work on the Udacity-style project write-up","commenter",[67,68],{"id":57,"by":58,"text":59},{"id":69,"by":70,"text":71},"15586970","abhinavkulkarni","Very good summary.",[73,81],{"value":74,"source":65,"evidence":75},"HOG + SVM is slow and less accurate than deep learning approaches",[76,77],{"id":57,"by":58,"text":59},{"id":78,"by":79,"text":80},"15584488","lxtx","Totally agree with your point on HOG + SVM, I think it is obsoleted by convolutional neural networks. I wrote a realtime human detection library [1] for a robotics project that…",{"value":82,"source":65,"evidence":83},"Standardizing data before the train\u002Ftest split leaks information",[84],{"id":85,"by":86,"text":87},"15586175","eggie5","I noticed you are standardizing your dataset before your test\u002Ftrain split. This is an example of information leakage which is causing your model to overfit by learning the test…",[89],{"value":90,"source":65,"evidence":91},"Write-up of the approach",[92,96],{"id":93,"by":94,"text":95},"15583195","yelnatz","Got a write up?",{"id":97,"by":98,"text":99},"15584365","Winterflow3r","Also interested in a writeup!",[101],{"value":102,"source":65,"evidence":103},"What is space binning?",[104],{"id":105,"by":106,"text":107},"15584721","ivarv","This might be the wrong place to ask, but my search skills are failing me as I try to understand what \"Space binning\" (referred to in the README of the linked project) is. The…",[109,116],{"value":110,"source":65,"evidence":111},"Garmin Varia rearview radar",[112],{"id":113,"by":114,"text":115},"15585340","radix07","By all means I respect wanting to roll your own version of this. But if you would like to buy something to detect vehicles from your rear, there is something that already exists…",{"value":117,"source":65,"evidence":118},"Haar cascade vehicle detection with Hough lane detection",[119],{"id":120,"by":121,"text":122},"15583040","quasse","My friend and I did something similar using Haar Cascades for vehicle detection and Hough transforms to detect the lane lines. We used that to analyze dash cam videos and…",{"comments":33,"answered":33,"key":124},[],{"commenters":126,"max_depth":127,"maker_replies":33,"first_comment_mins":128,"lifespan_hours":129},16,4,94,15,[131,133,137,141,143,147,150,154,157,159,162,165,168,170,172,174,178,180,181,183,185],[120,33,43,132,121,33],"project\u002Fneutral\u002Fexecution",[134,38,31,135,136,33],"15584611","project\u002Fpositive\u002Fidea","escapologybb",[138,38,33,139,140,33],"15585221","commenter\u002Fneutral\u002Fdesign","nkristoffersen",[142,38,33,139,136,33],"15585295",[144,38,31,145,146,33],"15585224","maker\u002Fpositive\u002Fnone","Nilef",[148,38,43,149,136,33],"15585268","maker\u002Fneutral\u002Fnone",[151,38,33,152,153,33],"15585288","other\u002Fneutral\u002Fdocs","coredog64",[155,38,33,156,136,33],"15585312","other\u002Fpositive\u002Fdocs",[113,38,33,158,114,33],"other\u002Fcritical\u002Fidea",[160,38,33,161,136,33],"15585463","commenter\u002Fneutral\u002Fpricing",[163,38,33,164,114,33],"15586340","other\u002Fneutral\u002Fpricing",[166,34,31,135,167,33],"15583560","langitbiru",[57,34,38,169,58,33],"project\u002Fcritical\u002Fperformance",[78,34,33,171,79,33],"commenter\u002Fneutral\u002Fperformance",[69,34,31,173,70,33],"maker\u002Fpositive\u002Fdocs",[175,43,31,176,177,33],"15583000","maker\u002Fpositive\u002Fexecution","garyfirestorm",[93,43,43,179,94,33],"maker\u002Fneutral\u002Fdocs",[97,43,43,179,98,33],[105,127,43,182,106,33],"project\u002Fneutral\u002Fdocs",[85,31,38,184,86,33],"project\u002Fcritical\u002Fexecution",[186,31,43,179,187,33],"15586224","colmvp",[],[190,195,200,205,209,214],{"id":191,"name":192,"points":193,"category":194},"15594004","Frappe Charts",474,"dev_tools",{"id":196,"name":197,"points":198,"category":199},"15596304","Airborn",469,"productivity",{"id":201,"name":202,"points":203,"category":204},"15601027","\u002Fusr\u002Fbin\u002Fhtop",219,"infrastructure",{"id":206,"name":207,"points":208,"category":199},"15558057","Baby Buddy",172,{"id":210,"name":211,"points":212,"category":213},"15589742","Minimalchat",163,"web_saas",{"id":215,"name":216,"points":217,"category":194},"15584028","Utelly",133,false,"v2",{"id":221,"name":5,"line":6,"ai":218,"cat":20,"year":13,"points":14,"comments":15,"rec":28,"s":222,"top":18,"kw":223,"maker":11,"domain":10,"tier":19,"attempts":33,"strip":224,"url":9,"mix":225,"praise":64,"objection":74,"sub":21},15582714,0.18,[24,21,25,26,27],"350053000005105533313",[31,32,33,34],1793990965855]