import re
import zlib
import cv2
from scapy.all import *
pictures_directory = "/home/mh/Desktop/pictures"
faces_directory = "/home/mh/Desktop/faces"
pcap_file = "bhp.pcap"
def get_http_headers(http_payload):
    try:
        headers_raw = http_payload[:http_payload.index("\r\n\r\n")+2]
        headers = dict(re.findall(r'(?P<name>.*?):(?P<value>.*?)\r\n', headers_raw))
    except:
        return None
    if 'Content-Type' not in headers:
        return None
    return headers

def extract_image(headers, http_payload):
    image,image_type = None, None
    try:
        if 'image' in headers['Content-Type']:
            image_type = headers['Content-Type'].split('/')[1]
            image = http_payload[http_payload.index('\r\n\r\n')+4:]
            try:
                if 'Content-Encoding' in headers.keys():
                    if headers['Content-Encoding'] == 'gzip':
                        image = zlib.decompress(image, 16+zlb.MAX_WBITS)
                    elif headers['Content-Encoding'] == 'deflate':
                        image = zlib.decompress(image)
            except:
                pass
    except:
        return None, None
    return image, image_type



def face_detect(path, file_name):
    img = cv2.imread(path)
    cascade = cv2.CascadeClassifier('/home/mh/Desktop/haarcascade_upperbody.xml')
    rects = cascade.detectMultiScale(img, 1.3, 4, cv2.cv.CV_HAAR_SCALE_IMAGE, (20,20))
    if len(rects) == 0:
        return False
    rects[:, 2:] += rects[:, :2]
    for x1, y1, x2, y2 in rects:
        cv2.retangle(img, (x1, y1), (x2, y2), (127, 255,0), 2)
        cv2.imwrite('%s/%s-%s' % (FACES_DIR, PCAP, file_name), img)
    return True

def http_assembler(pcap_file):
    carved_images = 0
    faces_detected = 0
    a = rdpcap(pcap_file)
    sessions = a.sessions()
    for session in sessions:
        http_payload = ""
        for packet in sessions[session]:
            try:
                if packet[TCP].dport == 80 or packet[TCP].sport == 80:
                    # reassemble the stream
                    http_payload += str(packet[TCP].payload)
            except:
                pass
        headers = get_http_headers(http_payload)
        if headers is None:
            continue
        image,image_type = extract_image(headers,http_payload)
        if image is not None and image_type is not None:
            file_name = "%s-pic_carver_%d.%s" % (pcap_file,carved_images,image_type)
            fd = open("%s/%s" % (pictures_directory,file_name),"wb")
            fd.write(image)
            fd.close()
            carved_images += 1
            # now attempt face detection
            try:
                result = face_detect("%s/%s" % (pictures_directory,file_name),file_name)
                if result is True:
                    faces_detected += 1
            except:
                pass
    return carved_images, faces_detected

carved_images, faces_detected = http_assembler(pcap_file)
print "Extracted: %d images" % carved_images
print "Detected: %d faces" % faces_detected
