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import numpy as np
import cv2
import os
DIR = r"C:/Users/dilji/OneDrive/Documents/CodingFiles/codeInit/backend/imageModel/utils"
PROTOTEXT = os.path.join(DIR, r"models/colorization_deploy_v2.prototxt")
MODEL = os.path.join(DIR, r"models/colorization_release_v2.caffemodel")
POINTS = os.path.join(DIR, r"models/pts_in_hull.npy")
def colorize(image_path):
image_path = os.path.join(DIR, image_path)
print("[INFO] Loading model...")
net = cv2.dnn.readNetFromCaffe(prototxt=PROTOTEXT, caffeModel=MODEL)
pts = np.load(POINTS)
class8 = net.getLayerId("class8_ab")
conv8 = net.getLayerId("conv8_313_rh")
pts = pts.transpose().reshape(2, 313, 1, 1)
net.getLayer(class8).blobs = [pts.astype("float32")]
net.getLayer(conv8).blobs = [np.full([1, 313], 2.606, dtype="float32")]
print("[INFO] Loading image...")
image = cv2.imread(image_path)
scaled = image.astype("float32") / 255.0
lab = cv2.cvtColor(scaled, cv2.COLOR_BGR2LAB)
resized = cv2.resize(lab, (224, 224))
L = cv2.split(resized)[0]
L -= 50
print("[INFO] Colorizing image...")
net.setInput(cv2.dnn.blobFromImage(L))
ab = net.forward()[0, :, :, :].transpose((1, 2, 0))
ab = cv2.resize(ab, (image.shape[1], image.shape[0]))
L = cv2.split(lab)[0]
colorized = np.concatenate((L[:, :, np.newaxis], ab), axis=2)
colorized = cv2.cvtColor(colorized, cv2.COLOR_LAB2BGR)
colorized = np.clip(colorized, 0, 1)
colorized = (255*colorized)
colorized = colorized.astype(np.uint8)
cv2.imwrite(os.path.join(DIR, "colorized.jpg"), colorized)
return os.path.join(DIR, "colorized.jpg")
def save_image(image_data, path):
with open(os.path.join(DIR,path), "wb") as f:
for chunk in image_data.chunks():
f.write(chunk)
f.close()
return path
def cleanup():
if (os.path.exists(os.path.join(DIR, "input.jpg"))):
os.remove(os.path.join(DIR, "input.jpg"))
if (os.path.exists(os.path.join(DIR, "colorized.jpg"))):
os.remove(os.path.join(DIR, "colorized.jpg")) |