def write_to_file(image, arr, outfile, color):
upperLeft, bottomRight = radius.get_corners(radius.get_radius(image, arr), image.size)
for i in range(len(arr)):
for j in range(len(arr[i])):
if i < upperLeft[1] and i > bottomRight[1] and j < bottomRight[0] and j > upperLeft[0]:
outfile.write(str(arr[i][j][color]))
outfile.write(",")
outfile.write("\n")
def write_to_file(image, arr, outfile, color):
upperLeft, bottomRight = radius.get_corners(radius.get_radius(image, arr), image.size)
for i in range(len(arr)):
for j in range(len(arr[i])):
if i < upperLeft[1] and i > bottomRight[1] and j < bottomRight[0] and j > upperLeft[0]:
outfile.write(str(arr[i][j][color]))
outfile.write(",")
outfile.write("\n")
def cropAndResize(FILENAME, newSize):
img = Image.open(FILENAME).convert('RGB')
arr=np.array(np.asarray(img).astype('float'))
upperLeft, bottomRight = radius.get_corners(radius.get_radius(img, arr), img.size)
arr = arr[upperLeft[1]:bottomRight[1], upperLeft[0]:bottomRight[0]]
new_img = Image.fromarray(arr.astype('uint8'),'RGB')
new_img = new_img.resize((newSize,newSize))
return new_img
def cropAndResize(FILENAME, newSize):
img = Image.open(FILENAME).convert("RGB")
arr = np.array(np.asarray(img).astype("float"))
upperLeft, bottomRight = radius.get_corners(radius.get_radius(img, arr), img.size)
arr = arr[upperLeft[1] : bottomRight[1], upperLeft[0] : bottomRight[0]]
new_img = Image.fromarray(arr.astype("uint8"), "RGB")
new_img = new_img.resize((newSize, newSize))
return new_img
def cropAndResize(FILENAME, newSize):
img = Image.open(FILENAME).convert('RGB')
arr=np.array(np.asarray(img).astype('float'))
upperLeft, bottomRight = radius.get_corners(radius.get_radius(img, arr), img.size)
#crop array to space we want
arr = arr[upperLeft[1]:bottomRight[1], upperLeft[0]:bottomRight[0]]
#make new image
new_img = Image.fromarray(arr.astype('uint8'),'RGB')
new_img = new_img.resize((newSize,newSize))
#get the image we just saved into an array, normalize it, then make it again
arr=np.array(np.asarray(new_img).astype('float'))
normalize(arr)
new_img_norm = Image.fromarray(arr.astype('uint8'),'RGB')
return new_img, new_img_norm
def main():
norm_red = open("norm_and_red.txt", "w")
just_red = open("just_red.txt", "w")
norm_blue = open("norm_and_blue.txt", "w")
just_blue = open("norm_and_blue.txt", "w")
norm_green = open("norm_and_green.txt", "w")
just_green = open("just_green.txt", "w")
loadPath = "/Users/Carson/Desktop/training_set/original"
start = time.time()
count = 0
for x in range(10, 1000):
try:
red_arr, norm_red_arr, blue_arr, norm_blue_arr, green_arr, norm_green_arr = [],[],[],[],[],[]
FILENAME = loadPath + "/" + str(x) + "_right.jpeg"
img = Image.open(FILENAME).convert('RGB')
arr = np.array(np.asarray(img).astype('float'))
upperLeft, bottomRight = radius.get_corners(radius.get_radius(img, arr), img.size)
for i in range(int(upperLeft[1]), int(bottomRight[1] + 1)):
for j in range(int(upperLeft[0]), int(bottomRight[0] + 1)):
red_arr.append(str(int(arr[i][j][0])))
'''green_arr.append(str(int(arr[i][j][1])))
blue_arr.append(str(int(arr[i][j][2])))'''
'''normalize(arr)
for i in range(int(upperLeft[1]), int(bottomRight[1] + 1)):
for j in range(int(upperLeft[0]), int(bottomRight[0] + 1)):
norm_red_arr.append(str(int(arr[i][j][0])))
norm_green_arr.append(str(int(arr[i][j][1])))
norm_blue_arr.append(str(int(arr[i][j][2])))'''
just_red.write(",".join(red_arr) + "\n")
'''just_blue.write(",".join(blue_arr) + "\n")
just_green.write(",".join(green_arr) + "\n")
norm_red.write(",".join(norm_red_arr) + "\n")
norm_blue.write(",".join(norm_blue_arr) + "\n")
norm_green.write(",".join(norm_green_arr) + "\n")'''
red_arr, norm_red_arr, blue_arr, norm_blue_arr, green_arr, norm_green_arr = [],[],[],[],[],[]
FILENAME = loadPath = "/" + str(x) + "_left.jpeg"
img = Image.open(FILENAME).convert('RGB')
arr = np.array(np.asarray(img).astype('float'))
upperLeft, bottomRight = radius.get_corners(radius.get_radius(img, arr), img.size)
for i in range(int(upperLeft[1]), int(bottomRight[1] + 1)):
for j in range(int(upperLeft[0]), int(bottomRight[0] + 1)):
red_arr.append(str(int(arr[i][j][0])))
'''green_arr.append(str(int(arr[i][j][1])))
blue_arr.append(str(int(arr[i][j][2])))'''
'''normalize(arr)
for i in range(int(upperLeft[1]), int(bottomRight[1] + 1)):
for j in range(int(upperLeft[0]), int(bottomRight[0] + 1)):
norm_red_arr.append(str(int(arr[i][j][0])))
norm_green_arr.append(str(int(arr[i][j][1])))
norm_blue_arr.append(str(int(arr[i][j][2])))'''
just_red.write(",".join(red_arr) + "\n")
'''just_blue.write(",".join(blue_arr) + "\n")
just_green.write(",".join(green_arr) + "\n")
norm_red.write(",".join(norm_red_arr) + "\n")
norm_blue.write(",".join(norm_blue_arr) + "\n")
norm_green.write(",".join(norm_green_arr) + "\n")'''
count += 1
except IOError: pass#print("Skipping image " + x)
if count % 1 == 0:
print("Count =" + str(count))
print("Elapsed time = " + str(time.time() - start) + " seconds")
print("Estimated time = " + str((time.time()-start)/float(count)*100.0/60.0) + " minutes")
if count == 100: break
norm_red.close()
just_red.close()
norm_blue.close()
just_blue.close()
norm_green.close()
just_green.close()
def main():
norm_red = open("norm_and_red.txt", "w")
just_red = open("just_red.txt", "w")
norm_blue = open("norm_and_blue.txt", "w")
just_blue = open("norm_and_blue.txt", "w")
norm_green = open("norm_and_green.txt", "w")
just_green = open("just_green.txt", "w")
loadPath = "/Users/Carson/Desktop/training_set/original"
start = time.time()
count = 0
for x in range(10, 1000):
try:
red_arr, norm_red_arr, blue_arr, norm_blue_arr, green_arr, norm_green_arr = [],[],[],[],[],[]
FILENAME = loadPath + "/" + str(x) + "_right.jpeg"
img = Image.open(FILENAME).convert('RGB')
arr = np.array(np.asarray(img).astype('float'))
upperLeft, bottomRight = radius.get_corners(
radius.get_radius(img, arr), img.size)
for i in range(int(upperLeft[1]), int(bottomRight[1] + 1)):
for j in range(int(upperLeft[0]), int(bottomRight[0] + 1)):
red_arr.append(str(int(arr[i][j][0])))
'''green_arr.append(str(int(arr[i][j][1])))
blue_arr.append(str(int(arr[i][j][2])))'''
'''normalize(arr)
for i in range(int(upperLeft[1]), int(bottomRight[1] + 1)):
for j in range(int(upperLeft[0]), int(bottomRight[0] + 1)):
norm_red_arr.append(str(int(arr[i][j][0])))
norm_green_arr.append(str(int(arr[i][j][1])))
norm_blue_arr.append(str(int(arr[i][j][2])))'''
just_red.write(",".join(red_arr) + "\n")
'''just_blue.write(",".join(blue_arr) + "\n")
just_green.write(",".join(green_arr) + "\n")
norm_red.write(",".join(norm_red_arr) + "\n")
norm_blue.write(",".join(norm_blue_arr) + "\n")
norm_green.write(",".join(norm_green_arr) + "\n")'''
red_arr, norm_red_arr, blue_arr, norm_blue_arr, green_arr, norm_green_arr = [],[],[],[],[],[]
FILENAME = loadPath = "/" + str(x) + "_left.jpeg"
img = Image.open(FILENAME).convert('RGB')
arr = np.array(np.asarray(img).astype('float'))
upperLeft, bottomRight = radius.get_corners(
radius.get_radius(img, arr), img.size)
for i in range(int(upperLeft[1]), int(bottomRight[1] + 1)):
for j in range(int(upperLeft[0]), int(bottomRight[0] + 1)):
red_arr.append(str(int(arr[i][j][0])))
'''green_arr.append(str(int(arr[i][j][1])))
blue_arr.append(str(int(arr[i][j][2])))'''
'''normalize(arr)
for i in range(int(upperLeft[1]), int(bottomRight[1] + 1)):
for j in range(int(upperLeft[0]), int(bottomRight[0] + 1)):
norm_red_arr.append(str(int(arr[i][j][0])))
norm_green_arr.append(str(int(arr[i][j][1])))
norm_blue_arr.append(str(int(arr[i][j][2])))'''
just_red.write(",".join(red_arr) + "\n")
'''just_blue.write(",".join(blue_arr) + "\n")
just_green.write(",".join(green_arr) + "\n")
norm_red.write(",".join(norm_red_arr) + "\n")
norm_blue.write(",".join(norm_blue_arr) + "\n")
norm_green.write(",".join(norm_green_arr) + "\n")'''
count += 1
except IOError:
pass #print("Skipping image " + x)
if count % 1 == 0:
print("Count =" + str(count))
print("Elapsed time = " + str(time.time() - start) + " seconds")
print("Estimated time = " +
str((time.time() - start) / float(count) * 100.0 / 60.0) +
" minutes")
if count == 100: break
norm_red.close()
just_red.close()
norm_blue.close()
just_blue.close()
norm_green.close()
just_green.close()
