speed issue, 1FPS about handtracking HOT 9 CLOSED

import sys
from operator import itemgetter
import numpy as np
import cv2
'''
Function:
	calculate Intersect of Union
Input: 
	rect_1: 1st rectangle
	rect_2: 2nd rectangle
Output:
	IoU
'''
def IoU(rect_1, rect_2):
    x11 = rect_1[0]    # first rectangle top left x
    y11 = rect_1[1]    # first rectangle top left y
    x12 = rect_1[2]    # first rectangle bottom right x
    y12 = rect_1[3]    # first rectangle bottom right y
    x21 = rect_2[0]    # second rectangle top left x
    y21 = rect_2[1]    # second rectangle top left y
    x22 = rect_2[2]    # second rectangle bottom right x
    y22 = rect_2[3]    # second rectangle bottom right y
    x_overlap = max(0, min(x12,x22) -max(x11,x21))
    y_overlap = max(0, min(y12,y22) -max(y11,y21))
    intersection = x_overlap * y_overlap
    union = (x12-x11) * (y12-y11) + (x22-x21) * (y22-y21) - intersection
    if union == 0:
	return 0
    else:
        return float(intersection) / union
'''
Function:
	calculate Intersect of Min area
Input: 
	rect_1: 1st rectangle
	rect_2: 2nd rectangle
Output:
	IoM
'''
def IoM(rect_1, rect_2):
    x11 = rect_1[0]    # first rectangle top left x
    y11 = rect_1[1]    # first rectangle top left y
    x12 = rect_1[2]    # first rectangle bottom right x
    y12 = rect_1[3]    # first rectangle bottom right y
    x21 = rect_2[0]    # second rectangle top left x
    y21 = rect_2[1]    # second rectangle top left y
    x22 = rect_2[2]    # second rectangle bottom right x
    y22 = rect_2[3]    # second rectangle bottom right y
    x_overlap = max(0, min(x12,x22) -max(x11,x21))
    y_overlap = max(0, min(y12,y22) -max(y11,y21))
    intersection = x_overlap * y_overlap
    rect1_area = (y12 - y11) * (x12 - x11)
    rect2_area = (y22 - y21) * (x22 - x21)
    min_area = min(rect1_area, rect2_area)
    return float(intersection) / min_area
'''
Function:
	apply NMS(non-maximum suppression) on ROIs in same scale
Input:
	rectangles: rectangles[i][0:3] is the position, rectangles[i][4] is scale, rectangles[i][5] is score
Output:
	rectangles: same as input
'''
def NMS(rectangles,threshold,type):
    sorted(rectangles,key=itemgetter(4),reverse=True)
    result_rectangles = rectangles
    number_of_rects = len(result_rectangles)
    cur_rect = 0
    while cur_rect < number_of_rects : 
        rects_to_compare = number_of_rects - cur_rect - 1 
        cur_rect_to_compare = cur_rect + 1 
        while rects_to_compare > 0:
	    score = 0
	    if type == 'iou':
		score =  IoU(result_rectangles[cur_rect], result_rectangles[cur_rect_to_compare])
	    else:
		score =  IoM(result_rectangles[cur_rect], result_rectangles[cur_rect_to_compare])
            if score >= threshold:
                del result_rectangles[cur_rect_to_compare]      # delete the rectangle
                number_of_rects -= 1
            else:
                cur_rect_to_compare += 1    # skip to next rectangle            
            rects_to_compare -= 1
        cur_rect += 1   # finished comparing for current rectangle
    return result_rectangles

# parameters for generating detection output.
det_out_param = {
    'num_classes': num_classes,
    'share_location': share_location,
    'background_label_id': background_label_id,
    'nms_param': {'nms_threshold': 0.45, 'top_k': 400},
    'keep_top_k': 200,
    'confidence_threshold': 0.01,
    'code_type': code_type,
    }