[{"data":1,"prerenderedAt":175},["ShallowReactive",2],{"project-9774181":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":5,"maker":10,"posted_at":11,"year":12,"points":13,"comments":14,"rank_in_year":15,"shown_in_year":16,"top":17,"tier":18,"category":19,"subcategory":20,"format":21,"keywords":22,"reception":26,"sentiment":27,"stance_mix":28,"scored_comments":32,"aspects":33,"strip":36,"post_text":37,"what":38,"said":56,"maker_in_thread":96,"shape":98,"grid":102,"attempts":135,"same_week":136,"maker_shows":29,"maker_hidden":167,"reader_version":168,"card":169},"9774181","robots.ox.ac.uk","Semantic Image Segmentation Live Demo","title","Show HN: Semantic Image Segmentation Live Demo","http:\u002F\u002Fwww.robots.ox.ac.uk\u002F~szheng\u002Fcrfasrnndemo","refrigerator",1435176752,2015,65,13,425,2565,17,"notable","ai","image segmentation","web_app",[23,20,24,25],"semantic segmentation","conditional random field","object recognition","loved",0.397,{"positive":29,"neutral":30,"mixed":30,"critical":31},6,3,0,12,{"performance":34},{"positive":35,"critical":31},5,[35,30,35,35,31,30,30,30,30,35,30,35,35],null,{"problem":39,"audience":37,"pricing":37,"motivation":37,"time_to_build":37,"stack":53,"openness":54,"stage":55,"team_size":54},{"value":40,"source":41,"evidence":42},"Labels which pixels belong to which object classes in a submitted image","inferred",[43,45,49],{"id":44},"post",{"id":46,"by":47,"text":48},"9774608","fasouto","Surprisingly good :) http:\u002F\u002Fwww.robots.ox.ac.uk\u002F~szheng\u002Fcrfasrnndemo\u002Fclassify_url?imageurl=http%3A%2F%2Fi.huffpost.com%2Fgen%2F1478236%2Fthumbs%2Fs-DIRD6-large640.jpg",{"id":50,"by":51,"text":52},"9774333","tothepixel","The first thing I tried to do was find the edge cases for this. Impressively a sofa bike with people on it was mostly identified!…",[],"unknown","launched",{"praise":57,"objections":83,"requests":93,"questions":94,"alternatives":95},[58],{"value":59,"source":60,"evidence":61},"Results impressively accurate on many test images","commenter",[62,63,67,71,75,79],{"id":46,"by":47,"text":48},{"id":64,"by":65,"text":66},"9774582","hoverbear","Better than expected! http:\u002F\u002Fi.imgur.com\u002FzsNXxzx.jpg",{"id":68,"by":69,"text":70},"9774694","jones1618","What impressed me was being able to distinguish a horse from a cow in rodeo shots and for a bonus extract the human, too. The neural net sometimes balks when the furry quadrupeds…",{"id":72,"by":73,"text":74},"9775198","s0l1dsnak3123","Really impressive:…",{"id":76,"by":77,"text":78},"9774499","vmorgulis","Amazing! http:\u002F\u002Fwww.robots.ox.ac.uk\u002F~szheng\u002Fcrfasrnndemo\u002Fclassify_url?imageurl=http%3A%2F%2Fa.abcnews.com%2Fimages%2FInternational%2Fht_whale_onto_boat_100721_ssh.jpg",{"id":80,"by":81,"text":82},"9781353","matrix00121","This is really cool!",[84],{"value":85,"source":60,"evidence":86},"Struggles with overlapping animals and unusual shapes like patterned furniture",[87,88,89],{"id":68,"by":69,"text":70},{"id":50,"by":51,"text":52},{"id":90,"by":91,"text":92},"9774540","shkkmo","It did ok with a leopard print sofa :) http:\u002F\u002Fwww.robots.ox.ac.uk\u002F~szheng\u002Fcrfasrnndemo\u002Fclassify_url?imageurl=http%3A%2F%2Fep.yimg.com%2Fca%2FI%2Fkpupholstery_2063_603432 But not…",[],[],[],{"comments":31,"answered":31,"key":97},[],{"commenters":32,"max_depth":99,"maker_replies":31,"first_comment_mins":100,"lifespan_hours":101},2,30,26,[103,105,108,111,113,117,119,120,124,126,127,130,132],[46,31,35,104,47,31],"project\u002Fpositive\u002Fperformance",[106,31,30,107,47,31],"9775139","project\u002Fneutral\u002Fnone",[109,31,35,104,110,31],"9777801","dppatel",[64,112,35,104,65,31],1,[114,112,31,115,116,31],"9774947","commenter\u002Fneutral\u002Fnone","nacs",[50,99,30,118,51,31],"project\u002Fmixed\u002Fperformance",[90,30,30,118,91,31],[121,30,30,122,123,31],"9775742","project\u002Fneutral\u002Fperformance","a1369209993",[68,125,30,118,69,31],4,[72,35,35,104,73,31],[128,29,30,122,129,31],"9775396","pbhjpbhj",[76,131,35,104,77,31],7,[80,133,35,134,81,31],8,"project\u002Fpositive\u002Fnone",[],[137,142,147,152,157,162],{"id":138,"name":139,"points":140,"category":141},"9746188","Wayback HN",503,"learning_science",{"id":143,"name":144,"points":145,"category":146},"9744471","MapChat",205,"consumer_social",{"id":148,"name":149,"points":150,"category":151},"9763870","Hypatia 0.2",191,"games",{"id":153,"name":154,"points":155,"category":156},"9757555","WhatsApp for Desktop",120,"hardware",{"id":158,"name":159,"points":160,"category":161},"9746867","Servasm",117,"infrastructure",{"id":163,"name":164,"points":165,"category":166},"9747417","say_restyle",73,"dev_tools",false,"v2",{"id":170,"name":5,"line":6,"ai":167,"cat":19,"year":12,"points":13,"comments":14,"rec":26,"s":171,"top":17,"kw":172,"maker":10,"domain":5,"tier":18,"attempts":31,"strip":173,"url":9,"mix":174,"praise":59,"objection":85,"sub":20},9774181,0.4,[23,20,24,25],"5355033335355",[29,30,30,31],1793990926607]