surf = cv2.SURF(400)

#kp, descriptor = surf.detectAndCompute(cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY), None)

kp, descriptor = surf.detectAndCompute(frame, None)

if descriptor is None:

return -1

points = descriptor.shape[0]

matches = np.zeros((points,1))

best_poke_desc = np.zeros((points,151))

best_poke_desc[:,0] = 151;

for pt in range(0, points):

d = descriptor[pt,:].reshape(1,128)

for poke in range(1,151):

best_poke_desc[pt,poke] = np.min(sp.cdist(desc[poke],d,'Euclidean'))

matches[pt] = np.argmin(best_poke_desc[pt,:])

val, count = mstats.mode(matches)

if( count[0][0] < 4):

return -1

desc = prep.build_descriptors()

A = cv2.imread(file_name)

results = list()

frame = np.zeros((window,window,3))

for row in range(0, A.shape[0], window/5):

results.append('r')

for col in range(0, A.shape[1], window/5):

frame = A[row:row+window, col:col+window,:]

if frame.shape[0] != window or frame.shape[1] != window:

break

results.append(test_frame(frame,desc))

surf = cv2.SURF(400)

desc = list()

desc.append([0])

for p in range(1,151):

string = ''.join(['PokeSprites/', str(p),'.png'])

A = cv2.imread(string)

surf = cv2.SURF(400)

kp, descriptor = surf.detectAndCompute(cv2.cvtColor(A,cv2.COLOR_BGR2GRAY),None)

desc.append(descriptor)