rpotter.py

#!/usr/bin/python
# -*- coding: utf-8 -*-
'''
  _\
  \
O O-O
 O O
  O
  
Raspberry Potter
Ollivander - Version 0.2 
Use your own wand or your interactive Harry Potter wands to control the IoT.  
Copyright (c) 2016 Sean O'Brien.  Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
'''

import random
import numpy as np
import cv2
from cv2 import *
import picamera #only needed if using RPi camera module
import threading
import sys
import math
import time
import warnings
import os
from paho.mqtt import client as mqtt_client
from dotenv import load_dotenv

# MQTT Parameters
FIRST_RECONNECT_DELAY = 1
RECONNECT_RATE = 2
MAX_RECONNECT_COUNT = 100
MAX_RECONNECT_DELAY = 10

# Image Parameters
lk_params = dict( winSize  = (20,20),
                maxLevel = 0,
                criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.01))
blur_params = (5,5)
dilation_params = (5, 5)
movment_threshold = 2

# start capturing
CAM_W_RES=640
CAM_H_RES=480
POINT_COLOR=(0,0,255)
WAND_TRESHOLD = 100

ig = [[0] for x in range(20)]

warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning)

def on_connect(client, userdata, flags, rc):
        if rc == 0:
            print("Connected to MQTT Broker!")
        else:
            print("Failed to connect, return code %d\n", rc)

def connect_mqtt(broker, port):
    print("MQTT Connecting")
    client = mqtt_client.Client()
    client.on_connect = on_connect
    client.connect(broker, port)
    return client

def on_disconnect(client, userdata, rc):
    print("Disconnected with result code: %s", rc)
    reconnect_count, reconnect_delay = 0, FIRST_RECONNECT_DELAY
    while reconnect_count < MAX_RECONNECT_COUNT:
        print("Reconnecting in %d seconds...", reconnect_delay)
        time.sleep(reconnect_delay)

        try:
            client.reconnect()
            print("Reconnected successfully!")
            return
        except Exception as err:
            print("%s. Reconnect failed. Retrying...", err)

        reconnect_delay *= RECONNECT_RATE
        reconnect_delay = min(reconnect_delay, MAX_RECONNECT_DELAY)
        reconnect_count += 1
    print("Reconnect failed after %s attempts. Exiting...", reconnect_count)

def publish(client, spell):
    global topic
    result = client.publish(topic, spell)
    # result: [0, 1]
    status = result[0]
    if status == 0:
        print(f"Send `{spell}` to topic `{topic}`")
    else:
        print(f"Failed to send message to topic {topic}")

def decrease_brightness(img, value=50):
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    h, s, v = cv2.split(hsv)

    lim = 0 + value
    v[v <= lim ] = 0
    v[v > lim] -= value

    final_hsv = cv2.merge((h, s, v))
    img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR)
    return img

def Spell(spell):    
    #clear all checks
    ig = [[0] for x in range(15)] 
    #Invoke IoT (or any other) actions here
    cv2.putText(mask, spell, (5, 25),cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255,0,0))
    #renamed spell Aguamenti but kept Incendio naming - fix later
    print("CAST: %s" %spell)
    publish(client,spell)
    cv2.putText(frame, spell, (10,30), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (0, 0, 255), 2)

def IsGesture(a,b,c,d,i):
    #look for basic movements - TODO: trained gestures
    os.system('clear')
    print(f'Point {i}')
    if ((a<(c-5))&(abs(b-d)<2)):
        ig[i].append("left")
    elif ((c<(a-5))&(abs(b-d)<2)):
        ig[i].append("right")
    elif ((b<(d-5))&(abs(a-c)<5)):
        ig[i].append("up")
    elif ((d<(b-5))&(abs(a-c)<5)):
        ig[i].append("down")
    #check for gesture patterns in array
    astr = ''.join(map(str, ig[i]))
    if "rightrightupup" in astr:
        ig[i]=[]
        Spell("Lumos")
    elif "rightrightdowndown" in astr:
        ig[i]=[]
        Spell("Nox")
	#Colovaria spell removed
    #elif "leftdown" in astr:
    #    Spell("Colovaria")
    # elif "leftup" in astr:
    #     Spell("Aguamenti")
    print(astr)
    if len(ig[i]) > 10:
        ig[i]=[]

def capture_frame():
    _, frame = cam.read()
    cv2.flip(frame,1,frame)
    return frame

def adjust_contrast_brightness(img, contrast:float=1.0, brightness:int=0):
    """
    Adjusts contrast and brightness of an uint8 image.
    contrast:   (0.0,  inf) with 1.0 leaving the contrast as is
    brightness: [-255, 255] with 0 leaving the brightness as is
    """
    brightness += int(round(255*(1-contrast)/2))
    return cv2.addWeighted(img, contrast, img, 0, brightness)

def gen_frame_gray(frame):
    # Mask detection area if dmask is defined

    #frame_gray = decrease_brightness(frame_gray, value=30)
    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    #cv2.equalizeHist(frame_gray)
    frame_gray = cv2.GaussianBlur(frame_gray,blur_params,1.5)
    dilate_kernel = np.ones(dilation_params, np.uint8)
    frame_gray = cv2.dilate(frame_gray, dilate_kernel, iterations=1)
    frame_gray = adjust_contrast_brightness(frame_gray,contrast=1.1)
    # frame_clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8,8))
    # frame_gray = frame_clahe.apply(frame_gray)
    # dmask = np.zeros_like(frame_gray)
    # cv2.rectangle(dmask,(300,220),(680,320),255,cv2.FILLED)
    # frame_gray = cv2.bitwise_and(frame_gray,dmask)
    return frame_gray

def wand_overlay(f,points):
    f2 = f.copy()
    for i,p in enumerate(points):
        a,b = p.ravel()
        cv2.circle(f2,(a,b),5,POINT_COLOR,-1)
        cv2.putText(f2, str(i), (a,b), cv2.FONT_HERSHEY_SIMPLEX, 1.0, POINT_COLOR)
    return f2

def points_exist(points):
    if points is not None:
        if len(points) > 0:
            return True
    return False

def FindWand():
    global p0, cam, mask, ig
    try:
        start = time.time()
        frame = capture_frame()
        frame_gray = gen_frame_gray(frame)
        p0 = cv2.HoughCircles(frame_gray,cv2.HOUGH_GRADIENT,3,50,param1=340,param2=4,minRadius=3,maxRadius=15)
        if points_exist(p0):
            p0.shape = (p0.shape[1], 1, p0.shape[2])
            p0 = p0[:,:,0:2]
            adj_index=0
            for i,p in enumerate(p0):
                a,b = p.ravel()
                if not frame_gray[int(b)][int(a)] >= WAND_TRESHOLD:
                    p0 = np.delete(p0,i-adj_index,0)
                    adj_index=adj_index+1
            ig = [[0] for x in range(20)]
        mask = np.zeros_like(frame)
        end = time.time()
        print(f"FindWand Completed in {end - start} seconds.")
        threading.Timer(3, FindWand).start()
    except:
        e = sys.exc_info()[1]
        print("Error: %s" % e) 
        exit

def TrackWand():
    global cam, p0, mask
    FindWand()
    old_gray = None
    while True:
        try:
            start = time.time()
            frame = capture_frame()
            frame_gray = gen_frame_gray(frame)
            if old_gray is not None and points_exist(p0):
                p1, st, _ = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
                # p2 = cv2.HoughCircles(old_gray,cv2.HOUGH_GRADIENT,3,50,param1=240,param2=30,minRadius=4,maxRadius=10)
                # p2 = p2[:,:,0:2]
                # p2.shape = (p2.shape[1], 1, p2.shape[2])

                # for i,circles in enumerate(p2):
                #     a,b = circles.ravel()
                #     cv2.circle(frame,(a,b),5,color,-1)
                #     cv2.putText(frame, str(i), (a,b), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0,0,255))
                # cv2.imshow("Raspberry Potter", frame)

                
                # Select good points
                good_new = p1[st==1]
                good_old = p0[st==1]

                
                # draw the tracks
                for i,(new,old) in enumerate(zip(good_new,good_old)):
                    a,b = new.ravel()
                    c,d = old.ravel()
                    # only try to detect gesture on highly-rated points (below 10)
                    dist = math.hypot(a - c, b - d)
                    if (dist>movment_threshold):
                        cv2.line(mask, (a,b),(c,d),(0,255,0), 2)
                        IsGesture(a,b,c,d,i)
                    cv2.circle(frame,(a,b),5,POINT_COLOR,-1)
                    cv2.putText(frame, str(i), (a,b), cv2.FONT_HERSHEY_SIMPLEX, 1.0, POINT_COLOR) 
                p0 = good_new.reshape(-1,1,2)
            img = cv2.add(frame,mask)
                #cv2.putText(img, "Press ESC to close.", (5, 25),
                #    cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255,255,255))
                #cv2.imshow("img",img)
                
            #cv2.imshow("Raspberry Potter", frame)
            cv2.imshow("Raspberry Potter", img)
            # Now update the previous frame and previous points
            old_gray = frame_gray.copy()
            cv2.imshow("FrameGray", frame_gray)
            end = time.time()
            print(f"TrackWand Completed in {end - start} seconds.")
        except IndexError:
            print("Index error - Tracking")  
        except:
            e = sys.exc_info()[0]
            #print("Tracking Error: %s" % e)

        key = cv2.waitKey(20)
        if key in [27, ord('Q'), ord('q')]: # exit on ESC
            # cv2.destroyAllWindows()
            cam.release()
            break


print("Initializing Camera")
cam = cv2.VideoCapture(-1)
cam.set(3, CAM_W_RES)
cam.set(4, CAM_H_RES)

if __name__ == "__main__":
    load_dotenv()
    global topic
    topic = os.getenv('TOPIC')
    broker = os.getenv('BROKER')
    port = int(os.getenv('PORT'))

    print("Initializing mqtt client")
    client = connect_mqtt(broker, port)
    client.on_disconnect = on_disconnect

    print("Initializing point tracking")
    TrackWand()