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How to use match_r method in avocado

Best Python code snippet using avocado_python

anno_func.py

Source:anno_func.py

1import json2import pylab as pl3import random4import numpy as np5#import cv26import copy7type42="i2,i4,i5,il100,il60,il80,ip,p10,p11,p12,p19,p23,p26,p27,p3,p5,p6,pg,ph4,ph4.5,ph5,pl100,pl120,pl20,pl30,pl40,pl5,pl50,pl60,pl70,pl80,pm20,pm30,pm55,pn,pne,pr40,w13,w32,w55,w57,w59"8type42 = type42.split(',')9def rect_cross(rect1, rect2):10    rect = [max(rect1[0], rect2[0]),11            max(rect1[1], rect2[1]),12            min(rect1[2], rect2[2]),13            min(rect1[3], rect2[3])]14    rect[2] = max(rect[2], rect[0])15    rect[3] = max(rect[3], rect[1])16    return rect17def rect_area(rect):18    return float(max(0.0, (rect[2]-rect[0])*(rect[3]-rect[1])))19def calc_cover(rect1, rect2):20    crect = rect_cross(rect1, rect2)21    return rect_area(crect) / rect_area(rect2)22def calc_iou(rect1, rect2):23    crect = rect_cross(rect1, rect2)24    ac = rect_area(crect)25    a1 = rect_area(rect1)26    a2 = rect_area(rect2)27    return ac / (a1+a2-ac)28def get_refine_rects(annos, raw_rects, minscore=20):29    cover_th = 0.530    refine_rects = {}31    for imgid in raw_rects.keys():32        v = raw_rects[imgid]33        tv = copy.deepcopy(sorted(v, key=lambda x:-x[2]))34        nv = []35        for obj in tv:36            rect = obj[1]37            rect[2]+=rect[0]38            rect[3]+=rect[1]39            if rect_area(rect) == 0: continue40            if obj[2] < minscore: continue41            cover_area = 042            for obj2 in nv:43                cover_area += calc_cover(obj2[1], rect)44            if cover_area < cover_th:45                nv.append(obj)46        refine_rects[imgid] = nv47    results = {}48    for imgid, v in refine_rects.items():49        objs = []50        for obj in v:51            mobj = {"bbox":dict(zip(["xmin","ymin","xmax","ymax"], obj[1])), 52                    "category":annos['types'][int(obj[0]-1)], "score":obj[2]}53            objs.append(mobj)54        results[imgid] = {"objects":objs}55    results_annos = {"imgs":results}56    return results_annos57def box_long_size(box):58    return max(box['xmax']-box['xmin'], box['ymax']-box['ymin'])59def eval_annos(annos_gd, annos_rt, iou=0.5, imgids=None, check_type=True, types=None, minscore=40, minboxsize=0, maxboxsize=512, match_same=True):60    ac_n, ac_c = 0,061    rc_n, rc_c = 0,062    if imgids==None:63        imgids = annos_rt['imgs'].keys()64    if types!=None:65        types = { t:0 for t in types }66    miss = {"imgs":{}}67    wrong = {"imgs":{}}68    right = {"imgs":{}}69    70    for imgid in imgids:71        v = annos_rt['imgs'][imgid]72        vg = annos_gd['imgs'][imgid]73        convert = lambda objs: [ [ obj['bbox'][key] for key in ['xmin','ymin','xmax','ymax']] for obj in objs]74        objs_g = vg["objects"]75        objs_r = v["objects"]76        bg = convert(objs_g)77        br = convert(objs_r)78        79        match_g = [-1]*len(bg)80        match_r = [-1]*len(br)81        if types!=None:82            for i in range(len(match_g)):83                if not types.has_key(objs_g[i]['category']):84                    match_g[i] = -285            for i in range(len(match_r)):86                if not types.has_key(objs_r[i]['category']):87                    match_r[i] = -288        for i in range(len(match_r)):89            if objs_r[i].has_key('score') and objs_r[i]['score']<minscore:90                match_r[i] = -291        matches = []92        for i,boxg in enumerate(bg):93            for j,boxr in enumerate(br):94                if match_g[i] == -2 or match_r[j] == -2:95                    continue96                #if match_same and objs_g[i]['category'] != objs_r[j]['category']: continue97                tiou = calc_iou(boxg, boxr)98                if tiou>iou:99                    matches.append((tiou, i, j))100        matches = sorted(matches, key=lambda x:-x[0])101        for tiou, i, j in matches:102            if match_g[i] == -1 and match_r[j] == -1:103                match_g[i] = j104                match_r[j] = i105                106        for i in range(len(match_g)):107            boxsize = box_long_size(objs_g[i]['bbox'])108            erase = False109            if not (boxsize>=minboxsize and boxsize<maxboxsize):110                erase = True111            #if types!=None and not types.has_key(objs_g[i]['category']):112            #    erase = True113            if erase:114                if match_g[i] >= 0:115                    match_r[match_g[i]] = -2116                match_g[i] = -2117        118        for i in range(len(match_r)):119            boxsize = box_long_size(objs_r[i]['bbox'])120            if match_r[i] != -1: continue121            if not (boxsize>=minboxsize and boxsize<maxboxsize):122                match_r[i] = -2123                    124        miss["imgs"][imgid] = {"objects":[]}125        wrong["imgs"][imgid] = {"objects":[]}126        right["imgs"][imgid] = {"objects":[]}127        miss_objs = miss["imgs"][imgid]["objects"]128        wrong_objs = wrong["imgs"][imgid]["objects"]129        right_objs = right["imgs"][imgid]["objects"]130        131        tt = 0132        for i in range(len(match_g)):133            if match_g[i] == -1:134                miss_objs.append(objs_g[i])135        for i in range(len(match_r)):136            if match_r[i] == -1:137                obj = copy.deepcopy(objs_r[i])138                obj['correct_catelog'] = 'none'139                wrong_objs.append(obj)140            elif match_r[i] != -2:141                j = match_r[i]142                obj = copy.deepcopy(objs_r[i])143                if not check_type or objs_g[j]['category'] == objs_r[i]['category']:144                    right_objs.append(objs_r[i])145                    tt+=1146                else:147                    obj['correct_catelog'] = objs_g[j]['category']148                    wrong_objs.append(obj)149                    150        151        rc_n += len(objs_g) - match_g.count(-2)152        ac_n += len(objs_r) - match_r.count(-2)153        154        ac_c += tt155        rc_c += tt156    if types==None:157        styps = "all"158    elif len(types)==1:159        styps = types.keys()[0]160    elif not check_type or len(types)==0:161        styps = "none"162    else:163        styps = "[%s, ...total %s...]"%(types.keys()[0], len(types))164    report = "iou:%s, size:[%s,%s), types:%s, accuracy:%s, recall:%s"% (165        iou, minboxsize, maxboxsize, styps, 1 if ac_n==0 else ac_c*1.0/ac_n, 1 if rc_n==0 else rc_c*1.0/rc_n)166    summury = {167        "iou":iou,168        "accuracy":1 if ac_n==0 else ac_c*1.0/ac_n,169        "recall":1 if rc_n==0 else rc_c*1.0/rc_n,170        "miss":miss,171        "wrong":wrong,172        "right":right,173        "report":report174    }...

maximum_bipartite_matching.py

Source:maximum_bipartite_matching.py

1# Python program to find2# maximal Bipartite matching.3class GFG:4    def __init__(self, graph):5        self.graph = graph  # residual graph6        self.ppl = len(graph)  # applicantã®æ°7        self.jobs = len(graph[0])  # jobã®æ°8    def bpm(self, u, match_r, visited):9        """10        u(applicant)ã¨é£æ¥ããå¨ã¦ã®v(job)ã«ã¤ãã¦ã11        """12        for v in range(self.jobs):13            if self.graph[u][v] and not visited[v]:14                visited[v] = True15                # v(job)ã¨ãããã³ã°ããäººãããªãããããã¯vã¨ãããã³ã°ããäººãä»ã®vã¨ãããã³ã°ãããããããvã¨uããããã³ã°ããã16                if match_r[v] == -1 or self.bpm(match_r[v], match_r, visited):17                    match_r[v] = u18                    return True19        return False20    def max_bpm(self):21        match_r = [-1] * self.jobs22        result = 023        for i in range(self.ppl):24            visited = [False] * self.jobs25            if self.bpm(i, match_r, visited):26                result += 127        return result28bpGraph = [[0, 1, 1, 0, 0, 0],29           [1, 0, 0, 1, 0, 0],30           [0, 0, 1, 0, 0, 0],31           [0, 0, 1, 1, 0, 0],32           [0, 0, 0, 0, 0, 0],33           [0, 0, 0, 0, 0, 1]]34g = GFG(bpGraph)35print("Maximum number of applicants that can get job is %d " % g.max_bpm())...

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