import json
import shutil
import os
import numpy as np
source_path = '/srv/ftp/hummingbird/2021'
#target_path = '/home/thebears/Videos/ftp'
target_path = '/home/thebears/data/ftplinks'
import scipy.stats
target_mean = 0.4
target_std = 1

gauss = scipy.stats.norm(target_mean, target_std)

have_json = set()
for di, _, fns in os.walk(source_path):
    for fn in fns:
        if fn.endswith('.json'):
            have_json.add(os.path.join(di, fn))




def box_area(box):
   return  (box[3]-box[1]) * (box[2] - box[0]) / 100000


do_stop = False
fracs = dict()

saveo = None
saveb = None

def gaussian(x, mu = target_mean, sig = target_std):
    return np.exp(-np.power(x - mu, 2.) / (2 * np.power(sig, 2.)))

scc = list()
for c_js in have_json:
    hits = 0
    total = 0
    o = json.load(open(c_js,'r'))
    if c_js.endswith('Hummingbird_01_20210701105440.json'):
        saveo = o

    if c_js.endswith('Hummingbird_01_20210627111405.json'):
        saveb = o

    avg = 0
    max_sc = 0

    for i in o:
#        for x,b in zip(i['scores'], i['boxes']):
#            scc.append((x,box_area(b)))
        
        if len(i['scores']) > 0:
            css = max(i['scores']) 
            mf = gaussian(box_area(i['boxes'][0]))
            avg += css * mf / len(o)


    fracs[c_js] = avg




ratios = dict()
for x,y in fracs.items():
    ratios[x] = y



    
sorted_ratios = {x:ratios[x] for x in sorted(ratios, key=lambda x: ratios[x])}


import shutil
for d in os.listdir(target_path):
    shutil.rmtree(target_path + '/' + d)



import math
dir_created = set()
for idx, (fname, ratio) in enumerate(sorted_ratios.items()):
    cr = math.floor(100*ratio)
    target_dir = os.path.join(target_path, '{0:02g}'.format(cr))
    if not os.path.exists(target_dir) and target_dir not in dir_created:
        os.mkdir(target_dir)
        dir_created.add(target_dir)
    else:
        dir_created.add(target_dir)
        

    
    source_file = fname.replace('.json','.mp4')
    target_file = os.path.join(target_dir, os.path.basename(source_file))
  
    
    os.symlink(source_file, target_file)

    source_file = fname.replace('.json','.json')
    target_file = os.path.join(target_dir, os.path.basename(source_file))
    os.symlink(source_file, target_file)
# %%

if False:
    plt.close('all')
    inp = saveo

    sco = list()
    for x in inp:
        if len(x['scores']) > 0:
            cscore = max(x['scores'])
            ar = box_area(x['boxes'][0])/ 100000
        else:
            cscore = 0
            ar = 0
        sco.append((cscore, ar))

    plt.plot(sco)
 
# %%
    distr = np.asarray(scc)