import cv2
import matplotlib.pyplot as plt
import mahotas as mh
import numpy as np

%matplotlib inline

## read
## cv2 read BGR color, but most other libraries read RGB, so convert
im = cv2.imread("data/images/beach.png")[:,:,::-1]
print im.shape
print im.dtype
print im.min(), im.max()

## display
plt.imshow(im)

## otherwise ...
plt.imshow(im[:,:,::-1])

## read as gray scale directly
im_gray = cv2.imread("data/images/trex.png", cv2.IMREAD_GRAYSCALE)
print im_gray.shape
print im_gray.dtype
print im_gray.min(), im_gray.max()
plt.imshow(im_gray, cmap = plt.cm.gray)

## interactive - but got some problems with ipython notebook display system
cv2.imshow("dianosou", im)
cv2.waitKey()

## convert to other formats
## convert from BGR to RGB again!!
cv2.imwrite("data/images/beach.bmp", im[:,:,::-1])
!file data/images/beach.bmp
!file data/images/beach.png

## manipulate pixles - cv2 store them as bgr instead of rgb
imm = im.copy()
imm[:, :, 2] = 255
plt.imshow(imm)

## manipulate pixles 
imm = im.copy()
imm[:100, :50] = (255, 0, 0) # red corner
plt.imshow(imm)

imm = im.copy()
## params: img, (x1, y1), (x2, y2), color (of the current img channel repr.)
cv2.line(imm, (0, 0), (100, 150), (255, 0, 0), ) #red line
cv2.circle(imm, (200, 100), 20, color = (0, 0, 255), thickness=5) #blue circle
## filled rectangle
cv2.rectangle(imm, (100, 50), (150, 120), color = (0, 255, 0), thickness = -1)
plt.imshow(imm)




imm = im.copy().astype(np.uint16)

cv2.rectangle(imm, (100, 50), (150, 120), 
              color = (0, 255, 0), thickness = -1)
plt.imshow(imm)

## it only works with np.unit8 
imm = im.copy().astype(np.int64)

cv2.rectangle(imm, (100, 50), (150, 120), 
              color = (0, 255, 0), thickness = -1)
plt.imshow(imm)

## canvas drawing - RGB because we are gonna use plt to plot
canvas = np.zeros((100, 100, 3), dtype=np.uint8)
## draw 25 random circles

centers = np.random.randint(10, 90, size = (25, 2))
radius = np.random.randint(1, 50, size = 25)
colors = np.random.randint(0, 256, size = (25, 3))
for c, r, col in zip(centers, radius, colors):
    ## somehow cv2 insists on tuples as control parameters
    cv2.circle(canvas, tuple(c), r, tuple(col), thickness = -1)
plt.imshow(canvas)

trex = cv2.imread("data/images/trex.png")[:, :, ::-1]
shifted_trex = cv2.warpAffine(trex, 
               np.array([[1, 0, 30], 
                        [0, 1, 100]], 
                dtype = np.float),
               dsize = (trex.shape[1], trex.shape[0])) # right down shift
plt.imshow(trex)
plt.figure()
plt.imshow(shifted_trex)

trex = cv2.imread("data/images/trex.png")[:, :, ::-1]
center = trex.shape[1]/2, trex.shape[0]/2
M = cv2.getRotationMatrix2D(center, -90, 1.)
rotated_trex = cv2.warpAffine(trex, M, (trex.shape[1], trex.shape[0]))
plt.imshow(trex)
plt.figure()
plt.imshow(rotated_trex)

trex = cv2.imread("data/images/trex.png")[:, :, ::-1]
center = trex.shape[1]/2, trex.shape[0]/2
M = cv2.getRotationMatrix2D(center, 0, 0.3)
rotated_trex = cv2.warpAffine(trex, M, (trex.shape[1], trex.shape[0]))
plt.imshow(trex)
plt.figure()
plt.imshow(rotated_trex)
print rotated_trex.shape

trex = cv2.imread("data/images/trex.png")[:, :, ::-1]
width, height = int(trex.shape[1]*0.3), int(trex.shape[0]*0.3)
resized_trex = cv2.resize(trex, 
                          (width, height), 
                          interpolation = cv2.INTER_AREA,)
plt.imshow(trex)
plt.figure(figsize = (1.5, 1.5))
plt.imshow(resized_trex)
print resized_trex.shape

cv2.imwrite("data/images/small_trex.png", resized_trex)

trex = cv2.imread("data/images/trex.png")[:, :, ::-1]
fig, axes = plt.subplots(2, 2, figsize = (8, 8))

fig.tight_layout()

axes = axes.ravel()
axes[0].imshow(trex)
axes[1].imshow(trex[:, ::-1, :])
axes[2].imshow(trex[::-1, :, :])
axes[3].imshow(trex[::-1, ::-1, :])

a = cv2.add(trex, trex)
plt.imshow(a)
plt.figure()
b = trex + trex ## overflow
plt.imshow(b)
print a.min(), a.max()
print b.min(), b.max()

beach = cv2.imread("data/images/beach.png")[:,:,::-1]
plt.imshow(beach)
h, w = beach.shape[:-1]

canvas = np.zeros((h, w), dtype = np.uint8)
mask = cv2.circle(canvas, (w/2, h/2), 30, color = 255,thickness = -1)
plt.figure()
plt.imshow(mask, cmap = plt.cm.gray)

masked_beach = cv2.bitwise_and(beach, beach, mask = mask)
plt.figure()
plt.imshow(masked_beach)

wave = cv2.imread("data/images/wave.png")[:,:,::-1]
fig, axes = plt.subplots(2, 2, figsize = (8, 8))
axes = axes.ravel()

fig.tight_layout()
axes[0].imshow(wave)
axes[0].set_title("original")
axes[1].imshow(wave[:, :, 0], cmap = plt.cm.gray)
axes[1].set_title("red")
axes[2].imshow(wave[:, :, 1], cmap = plt.cm.gray)
axes[2].set_title("green")
axes[3].imshow(wave[:, :, 2], cmap = plt.cm.gray)
axes[3].set_title("blue")

## confusing, confusing, RGB, BGR, ...
plt.imshow(cv2.cvtColor(beach, cv2.COLOR_RGB2HSV)[:,:,::-1])