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FinalProjDriver.py
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FinalProjDriver.py
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import cv2
import numpy as np
from collections import deque
import copy
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from pathlib import Path
import pandas as pd
cap = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_SIMPLEX
#red, orange, yellow, green, blue, purple, pink
#i have RGB
#it goes BGR
#colors = [(38, 38, 255)]
colors = [(38, 38, 255), (19, 148, 249), (17, 250, 250), (17, 250, 48), (255, 207, 47), (255, 47, 165), (248, 107, 253), (208, 77, 255)]
colorIndx = 0
redPts = [deque(maxlen=1000)]
orangePts = [deque(maxlen=1000)]
yellowPts = [deque(maxlen=1000)]
greenPts = [deque(maxlen=1000)]
bluePts = [deque(maxlen=1000)]
purplePts = [deque(maxlen=1000)]
pinkPts = [deque(maxlen=1000)]
redIndx = 0
orangeIndx = 0
yellowIndx = 0
greenIndx = 0
blueIndx = 0
purpleIndx = 0
pinkIndx = 0
clearcolor = 0
color0 = 0
color1 = 0
color2 = 0
color3 = 0
color4 = 0
color5 = 0
color6 = 0
def find_histogram(clt):
numLabels = np.arange(0, len(np.unique(clt.labels_)) + 1)
(hist, _) = np.histogram(clt.labels_, bins=numLabels)
hist = hist.astype("float")
hist /= hist.sum()
return hist
def plot_colors2(hist, centroids):
bar = np.zeros((50, 300, 3), dtype="uint8")
startX = 0
for(percent, color) in zip(hist, centroids):
endX = startX + (percent * 300)
cv2.rectangle(bar, (int(startX), 0), (int(endX), 50), color.astype("uint8").tolist(), -1)
startX = endX
return bar, color, percent
while(1):
_, frame = cap.read()
jamDraw = frame.copy()
blackImg = np.zeros((512, 512, 3), np.uint8)
flippedIMG = cv2.flip(frame, 0)
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
#lowerRed = np.array([90, 100, 100])
#upperRed = np.array([100, 255, 255])
lowerRed = np.array([80, 250, 100])
upperRed = np.array([100, 250, 255])
#lowerRed = np.array([145, 100, 100])
#upperRed = np.array([175, 255, 255])
mask = cv2.inRange(hsv, lowerRed, upperRed)
kernel = np.ones((5, 5), np.uint8)
dilate = cv2.dilate(mask, kernel, iterations=2)
ret, thresh = cv2.threshold(dilate, 15, 275, cv2.THRESH_BINARY)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
#parameters: input, contours to be passed in, draw all contours (-1) or index to a specific one, color, thickness
img = cv2.drawContours(frame, contours, -1, (0, 255, 0), 3)
center = None
img2 = None
#drawing the colors to choose from
points = [redPts, orangePts, yellowPts, greenPts, bluePts, purplePts, pinkPts]
for i in range(len(points)):
for j in range(len(points[i])):
for k in range(1, len(points[i][j])):
if points[i][j][k-1] is None or points[i][j][k] is None:
continue
img2 = cv2.line(frame, points[i][j][k - 1], points[i][j][k], colors[i], 23)
img = cv2.putText(frame, "Sketch ", (160, 35), font, 1, (130, 100, 80), 1, cv2.LINE_AA)
img = cv2.putText(frame, "Your ", (280, 35), font, 1, (255, 207, 47), 1, cv2.LINE_AA)
img = cv2.putText(frame, "Mind!", (360, 35), font, 1, (205, 207, 47), 1, cv2.LINE_AA)
img = cv2.putText(frame, "Clear", (0, 55), font, 1, (255, 255, 255), 1, cv2.LINE_AA)
#clear
img = cv2.rectangle(frame, (0, 60), (80, 90), (255, 255, 255), -1)
#red
img = cv2.rectangle(frame, (80, 60), (160, 90), colors[0], -1)
#orange
img = cv2.rectangle(frame, (160, 60), (240, 90), colors[1], -1)
#yellow
img = cv2.rectangle(frame, (240, 60), (320, 90), colors[2], -1)
#green
img = cv2.rectangle(frame, (320, 60), (400, 90), colors[3], -1)
#blue
img = cv2.rectangle(frame, (400, 60), (480, 90), colors[4], -1)
#purple
img = cv2.rectangle(frame, (480, 60), (560, 90), colors[5], -1)
#pink
img = cv2.rectangle(frame, (560, 60), (650, 90), colors[6], -1)
#take picture
img = cv2.rectangle(frame, (560, 390), (650, 420), (255, 255, 255), 3)
img = cv2.rectangle(frame, (561, 391), (649, 419), (40, 40, 40), -1)
img = cv2.putText(frame, "Snapshot", (490, 460), font, 1, (255, 255, 255), 1, cv2.LINE_AA)
if len(contours) > 0:
M = cv2.moments(thresh)
if (M['m00'] > 0):
# calculate x,y coordinate of center
cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])
else:
cX, cY = 700, 700
cv2.circle(frame, (cX, cY), 5, (255, 255, 255), -1)
center = cX, cY
if center[1] <= 90:
if 0 <= center[0] <= 80:
redPts = [deque(maxlen=1000)]
orangePts = [deque(maxlen=1000)]
yellowPts = [deque(maxlen=1000)]
greenPts = [deque(maxlen=1000)]
bluePts = [deque(maxlen=1000)]
purplePts = [deque(maxlen=1000)]
pinkPts = [deque(maxlen=1000)]
redIndx = 0
orangeIndx = 0
yellowIndx = 0
greenIndx = 0
blueIndx = 0
purpleIndx = 0
pinkIndx = 0
clearcolor += 1
elif 80 <= center[0] <= 160:
colorIndx = 0
color0 += 1
elif 160 <= center[0] <= 240:
colorIndx = 1
color1 += 1
elif 240 <= center[0] <= 320:
colorIndx = 2
color2 += 1
elif 320 <= center[0] <= 400:
colorIndx = 3
color3 += 1
elif 400 <= center[0] <= 480:
colorIndx = 4
color4 += 1
elif 480 <= center[0] <= 560:
colorIndx = 5
color5 += 1
elif 560 <= center[0] <= 650:
colorIndx = 6
color6 += 1
elif center[1] >= 390:
if center[0] >= 560:
cv2.imwrite('jamDrawImg.jpg', img2)
drawing = cv2.imread('jamDrawImg.jpg')
drawing = drawing[90:390, 0:700]
drawing = cv2.cvtColor(drawing, cv2.COLOR_BGR2RGB)
drawing = drawing.reshape((drawing.shape[0] * drawing.shape[1], 3))
clt = KMeans(n_clusters=3)
clt.fit(drawing)
hist = find_histogram(clt)
bar, color, percent = plot_colors2(hist, clt.cluster_centers_)
##second histogram
drawing2 = cv2.imread('jamDrawImg.jpg')
drawing2 = drawing2[90:390, 0:700]
drawing2 = cv2.cvtColor(drawing2, cv2.COLOR_BGR2RGB)
drawing2 = drawing2.reshape((drawing2.shape[0] * drawing2.shape[1], 3))
clt2 = KMeans(n_clusters=8)
clt2.fit(drawing2)
hist2 = find_histogram(clt2)
bar2, color2, percent2 = plot_colors2(hist2, clt2.cluster_centers_)
val1 = hist[0]
val2 = hist[1]
val3 = hist[2]
a1 = min(val1, val2, val3)
a3 = max(val1, val2, val3)
a2 = (val1 + val2 + val3) - a1 - a3
ranks = ([a1, a2, a3])
tempo = ranks[0]
valence = ranks[1]
dance = ranks[2]
print('danceability: ' + str(dance))
angryMood = color0
neutralMood = color3 + color6
sadMood = color4 + color5
print('sad: ' + str(sadMood))
print('neutral: ' + str(neutralMood))
print('angry: ' + str(angryMood))
upperDance = dance + 0.002
lowerDance = dance - 0.002
#data_path = Path('.') / 'Data'
#data_files = list(data_path.glob("*.xlsx"))
#data_pathMood = Path('.') / 'SecondData'
#data_filesMood = list(data_pathMood.glob("*.xlsx"))
df = pd.read_excel('cleanedMusicData.xlsx', 'Sheet1')
dfMood = pd.read_excel('HPI-Countries.xlsx', 'Sheet1')
#fileMood = data_filesMood[0]
#dfMood = pd.read_excel(str(fileMood))
#file = data_files[0]
#df = pd.read_excel(str(file))
df_dance = df[(df.danceability >= lowerDance) & (df.danceability <= upperDance)]
moodVals = [sadMood, neutralMood, angryMood]
sortedMood = sorted(moodVals)
if(sortedMood[2] == sadMood):
HPI_r = dfMood[(dfMood.HPI_Rank > 50) & (dfMood.HPI_Rank < 70)]
elif(sortedMood[2] == neutralMood):
HPI_r = dfMood[(dfMood.HPI_Rank > 0) & (dfMood.HPI_Rank < 50)]
elif(sortedMood[2] == angryMood):
HPI_r = dfMood[(dfMood.HPI_Rank > 70)]
finalMoodCOuntry = HPI_r[0:1]
print("You should live here: ")
print(finalMoodCOuntry['Country'])
finalSong_df = df_dance[0:10]
print('Here are 10 songs that represent your drawing: ')
for i in range(0, 10):
dateValues = finalSong_df[i:i+1]
songTitle = dateValues['title']
artist = dateValues['artist']
print('Song: ' + songTitle.astype(str) + " by " + artist.astype(str))
plt.axis("off")
plt.imshow(bar)
#plt.imshow(bar2)
plt.show()
break
else:
if colorIndx == 0:
redPts[redIndx].appendleft(center)
elif colorIndx == 1:
orangePts[orangeIndx].appendleft(center)
elif colorIndx == 2:
yellowPts[yellowIndx].appendleft(center)
elif colorIndx == 3:
greenPts[greenIndx].appendleft(center)
elif colorIndx == 4:
bluePts[blueIndx].appendleft(center)
elif colorIndx == 5:
purplePts[purpleIndx].appendleft(center)
elif colorIndx == 6:
pinkPts[pinkIndx].appendleft(center)
else:
redPts.append(deque(maxlen=1000))
redIndx += 1
orangePts.append(deque(maxlen=1000))
orangeIndx += 1
yellowPts.append(deque(maxlen=1000))
yellowIndx += 1
greenPts.append(deque(maxlen=1000))
greenIndx += 1
bluePts.append(deque(maxlen=1000))
blueIndx += 1
purplePts.append(deque(maxlen=1000))
purpleIndx += 1
pinkPts.append(deque(maxlen=1000))
pinkIndx += 1
cv2.imshow("Frame", frame)
k = cv2.waitKey(5) & 0xff
if k == 27:
break
cv2.destroyAllWindows()