import argparse

from models import *

from project.datasets import *

from project.utils import *

import cv2

import os

from project.grab_cut import seg

import sys

import math

import numpy as np

import tflearn

from tflearn.layers.core import input_data, dropout, fully_connected

from tflearn.layers.conv import conv_2d, max_pool_2d, avg_pool_2d, global_avg_pool

from tflearn.layers.normalization import local_response_normalization, batch_normalization

from tflearn.layers.merge_ops import merge

from tflearn.layers.estimator import regression

################################################################################

def construct_inceptionv1onfire (x,y, training=False):

return model

################################################################################

def construct_inceptionv3onfire(x,y, training=False, enable_batch_norm=True):

return model

################################################################################

# InceptionV4 : definition of inception_block_a

def inception_block_a(input_a):

return inception_a

################################################################################

# InceptionV4 : definition of reduction_block_a

def reduction_block_a(reduction_input_a):

return reduction_a

################################################################################

# InceptionV4 : definition of inception_block_b

def inception_block_b(input_b):

return inception_b_output

################################################################################

# InceptionV4 : definition of reduction_block_b

def reduction_block_b(reduction_input_b):

return reduction_b_output

################################################################################

# InceptionV4 : defintion of inception_block_c

def inception_block_c(input_c):

return inception_c_output

################################################################################

def construct_inceptionv4onfire(x,y, training=False, enable_batch_norm=True):

return model

def boxhandler(bbox):

return bbox

def boxcover(image,box,cut):

return image

def detect():

print('Done. (%.3fs)' % (time.time() - t0))

def imagedetect(cut):

print('done')

if __name__ == '__main__':

parser = argparse.ArgumentParser()

parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='*.cfg path')

parser.add_argument('--names', type=str, default='data/fires.names', help='*.names path')

parser.add_argument('--weights', type=str, default='weights/fire_lamp.pt', help='weights path')

parser.add_argument('--source', type=str, default='data/samples', help='source') # input file/folder, 0 for webcam

parser.add_argument('--output', type=str, default='output', help='output folder') # output folder

parser.add_argument('--img-size', type=int, default=512, help='inference size (pixels)')

parser.add_argument('--conf-thres', type=float, default=0.01, help='object confidence threshold')

parser.add_argument('--iou-thres', type=float, default=0.6, help='IOU threshold for NMS')

parser.add_argument('--fourcc', type=str, default='mp4v', help='output video codec (verify ffmpeg support)')

parser.add_argument('--half', action='store_true', help='half precision FP16 inference')

parser.add_argument('--device', default='', help='device id (i.e. 0 or 0,1) or cpu')

parser.add_argument('--view-img', action='store_true', help='display results')

parser.add_argument('--save-txt', action='store_true', help='save results to *.txt')

parser.add_argument('--classes', nargs='+', type=int, help='filter by class')

parser.add_argument('--agnostic-nms', action='store_true', help='class-agnostic NMS')

parser.add_argument('--augment', action='store_true', help='augmented inference')

parser.add_argument('--Source', type=str, default='output', help='source')

parser.add_argument('--savetxt', action='store_true',help='save output')

parser.add_argument('--saveimg', action='store_true',help='save img')

parser.add_argument('--FLremove',action='store_true',help='remove firelike')

parser.add_argument('--grabcut', action='store_true', help='grabcut')

parser.add_argument('--imgnum', type=int, default=-1)

parser.add_argument('--Output', type=str, default='output')

opt = parser.parse_args()

opt.cfg = check_file(opt.cfg) # check file

opt.names = check_file(opt.names) # check file

source,Source, savetxt, saveimg, FLremove, imgnum,cut, Output = opt.source,opt.Source, opt.savetxt, opt.saveimg, opt.FLremove, opt.imgnum, opt.grabcut,opt.Output

#print(savetxt,saveimg,FLremove)

with torch.no_grad():

detect()

imagedetect(cut)