diff --git a/back-end/oop/1679752285000-PtrdXn.jpg b/back-end/oop/1679752285000-PtrdXn.jpg
deleted file mode 100644
index 34fde2bfd2c29ed121636f48fe8a7f6ef561bbc5..0000000000000000000000000000000000000000
Binary files a/back-end/oop/1679752285000-PtrdXn.jpg and /dev/null differ
diff --git a/back-end/oop/__pycache__/temp.cpython-310.pyc b/back-end/oop/__pycache__/temp.cpython-310.pyc
deleted file mode 100644
index 80e9d3c6bafd616416cfc9abb7112360dcd68819..0000000000000000000000000000000000000000
Binary files a/back-end/oop/__pycache__/temp.cpython-310.pyc and /dev/null differ
diff --git a/back-end/oop/download.json b/back-end/oop/download.json
deleted file mode 100644
index 1ad1f03e16a70843c2f6e797cc6dc8ddf05624c7..0000000000000000000000000000000000000000
--- a/back-end/oop/download.json
+++ /dev/null
@@ -1,11 +0,0 @@
-{
- "seller": "ssfshop",
- "brand": "beanpole",
- "product_list": [
- {
- "name": "남녀공용 베이직 피케 티셔츠 - 블랙",
- "url": "https://img.ssfshop.com/cmd/LB_750x1000/src/https://img.ssfshop.com/goods/BPBR/23/02/15/GM0023021581678_0_ORGINL_20230327140102442.jpg",
- "type_of_clothes": "top"
- }
- ]
-}
\ No newline at end of file
diff --git a/back-end/oop/main.py b/back-end/oop/main.py
deleted file mode 100644
index 85182ef080865d732d53b377ac735d34e18fc0b0..0000000000000000000000000000000000000000
--- a/back-end/oop/main.py
+++ /dev/null
@@ -1,37 +0,0 @@
-import sys
-import json
-
-import temp
-
-with open(sys.argv[1], 'r') as file:
- shoppingmall_data = json.load(file)
-
-seller_brand_path = shoppingmall_data["seller"]+"/"+shoppingmall_data["brand"]
-
-imageDownloder = temp.ImageDownloader()
-imageFactory = temp.ImageFactory()
-
-imageProcessor = temp.ImageProcessor()
-
-faceDetector = temp.FaceDetector()
-
-clothesDetector = temp.ClothesDetector()
-
-databaseManager = temp.DatabaseManager()
-
-for product in shoppingmall_data["product_list"]:
- save_path = seller_brand_path+"/"+product["name"]
- image_path = imageDownloder.download_image(product["url"], save_path, "original.jpg")
- image = imageFactory.create_image(image_path, None)
-
- result_image = imageProcessor.process(image)
-
- faceData = faceDetector.detectFace(image)
- face = faceData.getFace(1)
-
- clothesDataList = clothesDetector.localize_objects(image)
- clothes = clothesDataList.getClothes(product["type_of_clothes"])
- clothes.denormalizeByImageSize(image)
-
- databaseManager.insertToClothesDataCollection(image, result_image, face, clothes)
-
diff --git a/back-end/oop/test.py b/back-end/oop/test.py
deleted file mode 100644
index db2ff835430155cc6bc6b1949816e11677ee436c..0000000000000000000000000000000000000000
--- a/back-end/oop/test.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import temp
-
-imageFactory = temp.ImageFactory()
-#faceDetector = temp.FaceDetector()
-#boxDrower = temp.BoxDrower()
-clothesDetector = temp.ClothesDetector()
-imagepath = "/home/sang/automated_image_processing/automated_image_processing/automated_image_processing/back-end/oop/ssfshop/beanpole/남녀공용 베이직 피케 티셔츠 - 블랙/DallE.png"
-image = imageFactory.create_image(imagepath, None)
-
-clothesObjectsList = clothesDetector.localize_objects(image)
-clothes = clothesObjectsList.getClothes("top")
-print(clothes.left, clothes.top, clothes.right, clothes.bottom)
diff --git a/back-end/source_code/__pycache__/image_downloader.cpython-310.pyc b/back-end/source_code/__pycache__/image_downloader.cpython-310.pyc
deleted file mode 100644
index b22b37f2c5177c0d12005285aeda41bb80e66a03..0000000000000000000000000000000000000000
Binary files a/back-end/source_code/__pycache__/image_downloader.cpython-310.pyc and /dev/null differ
diff --git a/back-end/source_code/__pycache__/mask_processor.cpython-310.pyc b/back-end/source_code/__pycache__/mask_processor.cpython-310.pyc
deleted file mode 100644
index 059e8807aa94ab56022a9e15d9cae9e95aef6e4c..0000000000000000000000000000000000000000
Binary files a/back-end/source_code/__pycache__/mask_processor.cpython-310.pyc and /dev/null differ
diff --git a/back-end/source_code/__pycache__/outpainting_processor.cpython-310.pyc b/back-end/source_code/__pycache__/outpainting_processor.cpython-310.pyc
deleted file mode 100644
index 700c5f16e43cf60663ad82f80e8ed9b700c031d2..0000000000000000000000000000000000000000
Binary files a/back-end/source_code/__pycache__/outpainting_processor.cpython-310.pyc and /dev/null differ
diff --git a/back-end/source_code/__pycache__/temp.cpython-310.pyc b/back-end/source_code/__pycache__/temp.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..630b1700eb56ea666678bdd9b73e070fd9516619
Binary files /dev/null and b/back-end/source_code/__pycache__/temp.cpython-310.pyc differ
diff --git a/back-end/source_code/download.json b/back-end/source_code/download.json
index 4714007a643eaa636aed39ca9c468d31ffd07da2..00a7f864b42a139bc13d0c45989d67475cf62a1b 100644
--- a/back-end/source_code/download.json
+++ b/back-end/source_code/download.json
@@ -1,16 +1,16 @@
{
"seller": "ssfshop",
"brand": "beanpole",
- "image_list": [
+ "product_list": [
{
- "product_name": "남녀공용 베이직 피케 티셔츠 - 블랙",
- "image_url": "https://img.ssfshop.com/cmd/LB_750x1000/src/https://img.ssfshop.com/goods/BPBR/23/02/15/GM0023021581678_0_ORGINL_20230327140102442.jpg",
+ "name": "남녀공용 베이직 피케 티셔츠 - 블랙",
+ "url": "https://img.ssfshop.com/cmd/LB_750x1000/src/https://img.ssfshop.com/goods/BPBR/23/02/15/GM0023021581678_0_ORGINL_20230327140102442.jpg",
"type_of_clothes": "top"
},
{
- "product_name": "매직 써커 패턴 슬림핏 팬츠 - 네이비",
- "image_url": "https://img.ssfshop.com/cmd/LB_750x1000/src/https://img.ssfshop.com/goods/BPBR/23/02/28/GM0023022838172_0_ORGINL_20230302150258661.jpg",
- "type_of_clothes": "pants"
+ "name": "바서티 볼드 스트라이프 럭비 티셔츠 - 블루",
+ "url": "https://img.ssfshop.com/cmd/LB_750x1000/src/https://img.ssfshop.com/goods/BPBR/23/01/19/GM0023011962271_0_ORGINL_20230214162711402.jpg",
+ "type_of_clothes": "top"
}
]
}
\ No newline at end of file
diff --git a/back-end/source_code/image_downloader.py b/back-end/source_code/image_downloader.py
deleted file mode 100644
index aeb520d04441f649b2dd090f096e38885893d2cb..0000000000000000000000000000000000000000
--- a/back-end/source_code/image_downloader.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import requests
-import original_image
-import os
-
-def download_image(url, folder_path, file_name):
- response = requests.get(url)
- if response.status_code == 200:
- os.makedirs(folder_path, exist_ok=True)
- image_path = folder_path+"/"+file_name
- with open(image_path, 'wb') as file:
- file.write(response.content)
- return image_path
\ No newline at end of file
diff --git a/back-end/oop/magick.appimage b/back-end/source_code/magick.appimage
similarity index 100%
rename from back-end/oop/magick.appimage
rename to back-end/source_code/magick.appimage
diff --git a/back-end/source_code/main.py b/back-end/source_code/main.py
index c8830841a307783db797108d3c2d158a555f841f..f5d185c121db7a231a9b79bf42d2a8f77e72754b 100644
--- a/back-end/source_code/main.py
+++ b/back-end/source_code/main.py
@@ -1,26 +1,37 @@
-import image_downloader
-import mask_processor
-import outpainting_processor
-
-import os
-import sys
import json
-import cv2
+from modules import image_processor
+from modules import database
-with open(sys.argv[1], 'r') as file:
+with open("download.json", 'r') as file:
shoppingmall_data = json.load(file)
-ratio = 0
-new_folder = shoppingmall_data["seller"]+"/"+shoppingmall_data["brand"]
-os.makedirs(new_folder, exist_ok=True)
+seller_brand_path = shoppingmall_data["seller"]+"/"+shoppingmall_data["brand"]
+
+imageDownloder = image_processor.ImageDownloader()
+imageFactory = image_processor.ImageFactory()
+
+imageProcessor = image_processor.ImageProcessor()
+
+faceDetector = image_processor.FaceDetector()
+clothesDetector = image_processor.ClothesDetector()
+
+databaseManager = database.DatabaseManager()
+
+for product in shoppingmall_data["product_list"]:
+ save_path = "image_data/"+seller_brand_path+"/"+product["name"]
+ image_url = product["url"]
+ image_path = imageDownloder.download_image(image_url, save_path, "original.jpg")
+ image = imageFactory.create_image(image_path, None)
+
+ result_image = imageProcessor.process(image)
+
+ faceData = faceDetector.detectFace(image)
+ face = faceData.getFace(1)
+
+ clothesDataList = clothesDetector.localize_objects(image)
+ clothes = clothesDataList.getClothes(product["type_of_clothes"])
+ clothes.denormalizeByImageSize(image)
-for data in shoppingmall_data["image_list"]:
- image_url = data["image_url"]
- folder_name = new_folder+"/"+data["product_name"]
- original_image_path = image_downloader.download_image(image_url, folder_name, "original.jpg")
- mask = mask_processor.generate_mask_of(original_image_path)
- transparent_bordered_image = outpainting_processor.make_transparent_border(original_image_path, mask, ratio)
- dallE_image_path = outpainting_processor.outpaint_image_with_DallE(transparent_bordered_image, folder_name)
+ databaseManager.insertToClothesDataCollection(image, image_url, result_image, face, clothes)
- outpainting_processor.recover_orignal_image_size(original_image_path, dallE_image_path, transparent_bordered_image, ratio)
\ No newline at end of file
diff --git a/back-end/source_code/mask_processor.py b/back-end/source_code/mask_processor.py
deleted file mode 100644
index 74d283cb48b6f508bd0b1a424b4d4406b1b703d3..0000000000000000000000000000000000000000
--- a/back-end/source_code/mask_processor.py
+++ /dev/null
@@ -1,54 +0,0 @@
-import onnxruntime
-import cv2
-import numpy as np
-
-def generate_mask_of(original_image_cv):
-
- if type(original_image_cv) is str: #파일 경로를 입력했을 경우 처리
- original_image_cv = cv2.imread(original_image_cv)
-
- model = onnxruntime.InferenceSession('unet.onnx')
-
- original_height, original_width = original_image_cv.shape[0], original_image_cv.shape[1]
-
- mask = cv2.resize(original_image_cv, (320, 320))
-
- mask = mask.transpose((2, 0, 1)) # 채널 순서 변경
- mask = mask.astype(np.float32) / 255.0 # 정규화
- mask = np.expand_dims(mask, axis=0) # 배치 차원 추가
-
- # 모델 추론
- input_name = model.get_inputs()[0].name
- output_name = model.get_outputs()[0].name
- mask = model.run([output_name], {input_name: mask})[0]
-
- # 후처리
- mask = mask[0, 0, :, :] # 배치와 채널 차원 제거
- mask = cv2.resize(mask, (original_width, original_height)) # 원래 크기로 복원. 이 마스크는 확장 영역을 선택할 때 쓰임.
- mask = (mask > 0.5).astype(np.uint8) * 255 # 이진화
- #cv2.imwrite(folder_path+"/"+'mask.png', mask)
-
- box_dictionary = get_mask_box(mask)
- mask_dictionary = {
- "mask_image": mask,
- "box_x": box_dictionary["box_x"],
- "box_y": box_dictionary["box_y"],
- "box_w": box_dictionary["box_w"],
- "box_h": box_dictionary["box_h"]
- }
- return mask_dictionary
-
-def get_mask_box(mask):
- contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
- # 모든 객체의 윤곽선을 하나의 리스트로 병합
- all_contours = np.concatenate(contours)
- # 윤곽선을 감싸는 최소 사각형 좌표 계산
- box_x, box_y, box_w, box_h = cv2.boundingRect(all_contours)
- # 왼쪽 위를 기준으로 (x,y) 좌표, w(너비)와 h(높이) 형태로 결과 출력
- box_dictionary = {
- "box_x": box_x,
- "box_y": box_y,
- "box_w": box_w,
- "box_h": box_h
- }
- return box_dictionary
\ No newline at end of file
diff --git a/back-end/source_code/modules/__pycache__/database.cpython-310.pyc b/back-end/source_code/modules/__pycache__/database.cpython-310.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..daf78fc6d357189ed7fc3d346378efcf8b3de112
Binary files /dev/null and b/back-end/source_code/modules/__pycache__/database.cpython-310.pyc differ
diff --git a/back-end/source_code/modules/database.py b/back-end/source_code/modules/database.py
new file mode 100644
index 0000000000000000000000000000000000000000..f69842f4896062acafbafe52161481fcf7d955e5
--- /dev/null
+++ b/back-end/source_code/modules/database.py
@@ -0,0 +1,43 @@
+from pymongo import MongoClient
+
+class DatabaseManager:
+ def __init__(self):
+ self.client = MongoClient('mongodb://localhost:27017/')
+
+ def is_mongodb_running(self):
+ try:
+ self.client.server_info() # 서버 정보 요청
+ return True # 실행 중인 경우 True 반환
+ except:
+ return False
+ def insertToClothesDataCollection(self, orignalImage, imaga_url, finalImage, face, clothes):
+ db = self.client['fashionImageTest']
+ collection = db['clothesData']
+ inserted_data = {
+ "original_image": {
+ "file_path": orignalImage.filepath,
+ "url": imaga_url
+ },
+ "dalle_image_path": finalImage.filepath,
+ "dalle_image_width": finalImage.width,
+ "dalle_image_height": finalImage.height,
+ "x_offset": finalImage.x_offset,
+ "y_offset": finalImage.y_offset,
+ "face": {
+ "left_line_pixel": face.left + finalImage.x_offset,
+ "right_line_pixel": face.right + finalImage.x_offset,
+ "top_line_pixel": face.top + finalImage.y_offset,
+ "bottom_line_pixel": face.bottom + finalImage.y_offset,
+ },
+ "clothes": {
+ "type_of_clothes": clothes.type_of_clothes,
+ "left_line_pixel": clothes.left + finalImage.x_offset,
+ "right_line_pixel": clothes.right + finalImage.x_offset,
+ "top_line_pixel": clothes.top + finalImage.y_offset,
+ "bottom_line_pixel": clothes.bottom + finalImage.y_offset,
+ }
+ }
+ print(type(inserted_data["clothes"]["left_line_pixel"]))
+ print(inserted_data["clothes"]["left_line_pixel"])
+ insert_result = collection.insert_one(inserted_data)
+ print(f"Inserted document ID: {insert_result.inserted_id}")
\ No newline at end of file
diff --git a/back-end/source_code/modules/fileManager.py b/back-end/source_code/modules/fileManager.py
new file mode 100644
index 0000000000000000000000000000000000000000..bfbde175324be0a58073bc989489dee41f05f247
--- /dev/null
+++ b/back-end/source_code/modules/fileManager.py
@@ -0,0 +1,10 @@
+import requests
+class ImageDownloader:
+ def download_image(self, url, folder_path, file_name):
+ response = requests.get(url)
+ if response.status_code == 200:
+ os.makedirs(folder_path, exist_ok=True)
+ image_path = folder_path+"/"+file_name
+ with open(image_path, 'wb') as file:
+ file.write(response.content)
+ return image_path
diff --git a/back-end/oop/temp.py b/back-end/source_code/modules/image_processor.py
similarity index 67%
rename from back-end/oop/temp.py
rename to back-end/source_code/modules/image_processor.py
index dcfe6a2f1ce70a8f0889b9af8ee91ffc46cc39d7..9c02e77ae9e4a0571e3bb8930fe4f61c1fe5b0a0 100644
--- a/back-end/oop/temp.py
+++ b/back-end/source_code/modules/image_processor.py
@@ -1,22 +1,10 @@
-import requests
import cv2
import numpy as np
import onnxruntime
import os
import subprocess
-import temp
-
-class ImageDownloader:
- def download_image(self, url, folder_path, file_name):
- response = requests.get(url)
- if response.status_code == 200:
- os.makedirs(folder_path, exist_ok=True)
- image_path = folder_path+"/"+file_name
- with open(image_path, 'wb') as file:
- file.write(response.content)
- return image_path
-
+from modules import fileManager
class Image:
def __init__(self, filepath, cv_image):
@@ -27,6 +15,9 @@ class Image:
self.cv_image = cv2.imread(filepath)
self.height = self.cv_image.shape[0]
self.width = self.cv_image.shape[1]
+ self.url = None
+ def setURL(self, url):
+ self.url = url
class ImageFactory:
def create_image(self,filepath, cv_image):
image = Image(filepath, cv_image)
@@ -227,7 +218,7 @@ class ImageChopper:
object_move_x = paddedImage.x_offset
object_move_y = paddedImage.y_offset
- magick_command = SystemChecker.returnMagickCommand
+ magick_command = SystemChecker().returnMagickCommand()
if mask.smallest_box_x == 0:
subprocess.run([magick_command,"convert", "temp_alpha.png", "-gravity", "west", "-chop", (str(paddedImage.x_offset)+"x"+"0"), "temp_alpha.png"])
@@ -238,8 +229,9 @@ class ImageChopper:
if mask.smallest_box_x + mask.smallest_box_width + 10 >= mask.width:
subprocess.run([magick_command,"convert", "temp_alpha.png", "-gravity", "east", "-chop", (str(paddedImage.x_offset)+"x"+"0"), "temp_alpha.png"])
if mask.smallest_box_y + mask.smallest_box_height + 10 >= mask.height:
+ print(magick_command,"convert", "temp_alpha.png", "-gravity", "south", "-chop", ("0"+"x"+str(paddedImage.y_offset)), "temp_alpha.png")
subprocess.run([magick_command,"convert", "temp_alpha.png", "-gravity", "south", "-chop", ("0"+"x"+str(paddedImage.y_offset)), "temp_alpha.png"])
-
+
folder_path = os.path.dirname(image_path)
file_path = folder_path + "/result.png"
os.rename("temp_alpha.png", file_path)
@@ -248,44 +240,16 @@ class ImageChopper:
return result
-class Face:
- def __init__(self, left, top, right, bottom) -> None:
- self.left = left
- self.top = top
- self.right = right
- self.bottom = bottom
-class FaceDataList:
- def __init__(self, face_dict_data) -> None:
- self.data = face_dict_data
- def getFace(self, face_number):
- if type(self.data) is tuple:
- return (None, None)
- face_location = self.data["face_"+str(face_number)]["facial_area"]
- return Face(face_location[0], face_location[1], face_location[2], face_location[3])
-
-class FaceDetector:
- def detectFace(self,image):
- from retinaface import RetinaFace
- faceDataList = FaceDataList(RetinaFace.detect_faces(image.filepath))
- return faceDataList
-class BoxDrower:
- def drawBox(self, image, left_top, right_bottom):
- if left_top == None:
- print("there is no face")
- return
- face_bounding_box = image.cv_image.copy()
- cv2.rectangle(face_bounding_box, left_top, right_bottom, (0, 255, 0), 2)
- cv2.imwrite(os.path.dirname(image.filepath)+"/"+'face_bounding_box.jpg', face_bounding_box)
class ImageProcessor:
def __init__(self):
- self.maskGenerator = temp.MaskGenerator()
- self.paddedImageFactory = temp.PaddedImageFactory()
- self.dallEImageGenerator= temp.DallEImageGenerator()
- self.featheredImageFactory = temp.FeatheredImageFactory()
- self.alphaCompositer = temp.AlphaCompositer()
- self.imageChopper = temp.ImageChopper()
- self.imageDownloder = temp.ImageDownloader()
+ self.maskGenerator = MaskGenerator()
+ self.paddedImageFactory = PaddedImageFactory()
+ self.dallEImageGenerator= DallEImageGenerator()
+ self.featheredImageFactory = FeatheredImageFactory()
+ self.alphaCompositer = AlphaCompositer()
+ self.imageChopper = ImageChopper()
+ self.imageDownloder = fileManager.ImageDownloader()
def process(self, image):
mask = self.maskGenerator.create_mask(image)
padded_image = self.paddedImageFactory.create_padded_image(image, mask, 55)
@@ -294,79 +258,3 @@ class ImageProcessor:
resized_outpainted_image = self.alphaCompositer.alphaCompositingWithResizing(feathered_image, dallE_image)
result_image = self.imageChopper.chopInvadingBorderUsingMask(resized_outpainted_image, mask, image.filepath)
return result_image
-
-class ClothesDetector:
- def localize_objects(self, image):
- from google.cloud import vision
- client = vision.ImageAnnotatorClient()
-
- with open(image.filepath, 'rb') as image_file:
- content = image_file.read()
- image = vision.Image(content=content)
-
- objects = client.object_localization(
- image=image).localized_object_annotations
-
- return ClothesObjectsList(objects)
-class Clothes:
- def __init__(self, type_of_clothes, left, top, right, bottom) -> None:
- self.type_of_clothes = type_of_clothes
- self.normalized_left = left
- self.normalized_top = top
- self.normalized_right = right
- self.normalized_bottom = bottom
- self.left = None
- self.top = None
- self.right = None
- self.bottom = None
- def denormalizeByImageSize(self, image):
- self.left = int(self.normalized_left * image.width)
- self.top = int(self.normalized_top * image.height)
- self.right = int(self.normalized_right * image.width)
- self.bottom = int(self.normalized_bottom * image.height)
-
-class ClothesObjectsList:
- def __init__(self, objects) -> None:
- self.objects = objects
- def getClothes(self, type_of_clothes):
- for object_ in self.objects:
- if object_.name == type_of_clothes:
- break
- clothes_data_normalized_vertices = object_.bounding_poly.normalized_vertices
-
- normalized_clothes_left = clothes_data_normalized_vertices[0].x
- normalized_clothes_top = clothes_data_normalized_vertices[0].y
- normalized_clothes_right = clothes_data_normalized_vertices[2].x
- normalized_clothes_bottom = clothes_data_normalized_vertices[2].y
- return Clothes(type_of_clothes, normalized_clothes_left,normalized_clothes_top, normalized_clothes_right, normalized_clothes_bottom)
-
-class DatabaseManager:
- def __init__(self):
- from pymongo import MongoClient
- self.client = MongoClient('mongodb://localhost:27017/')
- def insertToClothesDataCollection(self, orignalImage, finalImage, face, clothes):
- db = self.client['fashionImageTest']
- collection = db['clothesData']
- inserted_data = {
- "original_image_path": orignalImage.filepath,
- "dalle_image_path": finalImage.filepath,
- "dalle_image_width": finalImage.width,
- "dalle_image_height": finalImage.height,
- "x_offset": finalImage.x_offset,
- "y_offset": finalImage.y_offset,
- "face": {
- "left_line_pixel": face.left + finalImage.x_offset,
- "right_line_pixel": face.right + finalImage.x_offset,
- "top_line_pixel": face.top + finalImage.y_offset,
- "bottom_line_pixel": face.bottop + finalImage.y_offset,
- },
- "clothes": {
- "type_of_clothes": clothes.type_of_clothes,
- "left_line_pixel": clothes.left + finalImage.x_offset,
- "right_line_pixel": clothes.right + finalImage.x_offset,
- "top_line_pixel": clothes.top + finalImage.y_offset,
- "bottom_line_pixel": clothes.bottop + finalImage.y_offset,
- }
- }
- insert_result = collection.insert_one(inserted_data)
- print(f"Inserted document ID: {insert_result.inserted_id}")
\ No newline at end of file
diff --git a/back-end/source_code/modules/object_detector.py b/back-end/source_code/modules/object_detector.py
new file mode 100644
index 0000000000000000000000000000000000000000..d8471fa5b42e2635889bace3e8e3ce9f142af0e4
--- /dev/null
+++ b/back-end/source_code/modules/object_detector.py
@@ -0,0 +1,76 @@
+import cv2
+import os
+
+class Face:
+ def __init__(self, left, top, right, bottom) -> None:
+ self.left = int(left)
+ self.top = int(top)
+ self.right = int(right)
+ self.bottom = int(bottom)
+class FaceDataList:
+ def __init__(self, face_dict_data) -> None:
+ self.data = face_dict_data
+ def getFace(self, face_number):
+ if type(self.data) is tuple:
+ return (None, None)
+ face_location = self.data["face_"+str(face_number)]["facial_area"]
+ return Face(face_location[0], face_location[1], face_location[2], face_location[3])
+
+class FaceDetector:
+ def detectFace(self,image):
+ from retinaface import RetinaFace
+ faceDataList = FaceDataList(RetinaFace.detect_faces(image.filepath))
+ return faceDataList
+class BoxDrower:
+ def drawBox(self, image, left_top, right_bottom):
+ if left_top == None:
+ print("there is no face")
+ return
+ face_bounding_box = image.cv_image.copy()
+ cv2.rectangle(face_bounding_box, left_top, right_bottom, (0, 255, 0), 2)
+ cv2.imwrite(os.path.dirname(image.filepath)+"/"+'face_bounding_box.jpg', face_bounding_box)
+
+class ClothesDetector:
+ def localize_objects(self, image):
+ from google.cloud import vision
+ client = vision.ImageAnnotatorClient()
+
+ with open(image.filepath, 'rb') as image_file:
+ content = image_file.read()
+ image = vision.Image(content=content)
+
+ objects = client.object_localization(
+ image=image).localized_object_annotations
+
+ return ClothesObjectsList(objects)
+class Clothes:
+ def __init__(self, type_of_clothes, left, top, right, bottom) -> None:
+ self.type_of_clothes = type_of_clothes
+ self.normalized_left = left
+ self.normalized_top = top
+ self.normalized_right = right
+ self.normalized_bottom = bottom
+ self.left = None
+ self.top = None
+ self.right = None
+ self.bottom = None
+ def denormalizeByImageSize(self, image):
+ self.left = int(self.normalized_left * image.width)
+ self.top = int(self.normalized_top * image.height)
+ self.right = int(self.normalized_right * image.width)
+ self.bottom = int(self.normalized_bottom * image.height)
+
+class ClothesObjectsList:
+ def __init__(self, objects) -> None:
+ self.objects = objects
+ def getClothes(self, type_of_clothes):
+ for object_ in self.objects:
+ if object_.name == type_of_clothes:
+ break
+ clothes_data_normalized_vertices = object_.bounding_poly.normalized_vertices
+
+ normalized_clothes_left = clothes_data_normalized_vertices[0].x
+ normalized_clothes_top = clothes_data_normalized_vertices[0].y
+ normalized_clothes_right = clothes_data_normalized_vertices[2].x
+ normalized_clothes_bottom = clothes_data_normalized_vertices[2].y
+ return Clothes(type_of_clothes, normalized_clothes_left,normalized_clothes_top, normalized_clothes_right, normalized_clothes_bottom)
\ No newline at end of file
diff --git a/back-end/source_code/original_image.py b/back-end/source_code/original_image.py
deleted file mode 100644
index f34ec2e6e0e58192649b927e1cde8ee825591b60..0000000000000000000000000000000000000000
--- a/back-end/source_code/original_image.py
+++ /dev/null
@@ -1,5 +0,0 @@
-
-original_image_height = 0
-original_image_width = 0
-outpaint_border_x_offset = 0
-outpaint_border_y_offset = 0
\ No newline at end of file
diff --git a/back-end/source_code/outpainting_processor.py b/back-end/source_code/outpainting_processor.py
deleted file mode 100644
index 2b521490928651f5dbb2ea2facfa68bd9dc9488a..0000000000000000000000000000000000000000
--- a/back-end/source_code/outpainting_processor.py
+++ /dev/null
@@ -1,127 +0,0 @@
-import mask_processor
-import cv2
-import numpy as np
-from dotenv import load_dotenv
-import os
-import openai
-import image_downloader
-
-def outpaint_image_with_DallE(bordered_image, folder_name):
-
- load_dotenv()
- openai.organization = os.getenv("ORG_ID")
- openai.api_key = os.getenv("API_KEY")
-
- cv2.imwrite("temp.png", bordered_image["transparent_bordered_image"])
- outpainted = openai.Image.create_edit(
- image = open("temp.png", "rb"),
- prompt="photo of person",
- n=1,
- size="1024x1024"
- )
- image_url = outpainted.data[0]['url']
- DallE_image_path = image_downloader.download_image(image_url, folder_name, "DallE.png" )
- return DallE_image_path
-
-def apply_feather(original_image_path):
- if type(original_image_path) is str:
- original = cv2.imread(original_image_path)
- feather = cv2.cvtColor(original, cv2.COLOR_BGR2BGRA)
- original_height = feather.shape[0]
- original_width = feather.shape[1]
-
- if feather.shape[0] >= original_width:
- border_size = int(0.05 * original_height)
- else:
- border_size = int(0.05 * original_width)
-
- for i in range(border_size):
- feather[ i,:, 3] = int(255* i/border_size)
- feather[-i,:, 3] = int(255* i/border_size)
- feather[:, i, 3] = int(255* i/border_size)
- feather[:,-i, 3] = int(255* i/border_size)
-
- feather[:border_size , :border_size, 3] = 0
- feather[:border_size , -border_size:, 3] = 0
- feather[-border_size:, -border_size:, 3] = 0
- feather[-border_size:, :border_size, 3] = 0
-
- for radius in range(0, border_size):
- for angle in range(0, 90 + 1):
- radian = np.deg2rad(angle)
- x = int(original_width- border_size + radius * np.cos(radian))
- y = int(original_height- border_size + radius * np.sin(radian))
- feather[y, x][3] = int(255 - 255* radius/border_size)
-
- for angle in range(90, 180 + 1):
- radian = np.deg2rad(angle)
- x = int(border_size + radius * np.cos(radian))
- y = int(original_height- border_size + radius * np.sin(radian))
- feather[y, x][3] = int(255 - 255* radius/border_size)
-
- for angle in range(180, 270 + 1):
- radian = np.deg2rad(angle)
- x = int(border_size + radius * np.cos(radian))
- y = int(border_size + radius * np.sin(radian))
- feather[y, x][3] = int(255-255* radius/border_size)
-
- for angle in range(270, 360 + 1):
- radian = np.deg2rad(angle)
- x = int(original_width - border_size + radius * np.cos(radian))
- y = int(border_size + radius * np.sin(radian))
- feather[y, x][3] = int(255 - 255* radius/border_size)
-
- return feather
-
-
-
-def recover_orignal_image_size(original_image_path, dallE_image_path, transparent_bordered_image, ratio):
- feather = apply_feather(original_image_path)
- # 아웃 페인팅 위에 기존 이미지 올리기
- ## 반투명 처리된 이미지 이용
-
- result = cv2.imread(dallE_image_path)
- new_length = int(1024*longer/ratio)
- result = cv2.resize(result, (new_length, new_length))
-
- cv2.imwrite(folder_path+"/"+"alpha_compistion.png", result)
-
- x_offset = int((new_length - original_width) / 2)
- y_offset = int((new_length - original_height) / 2)
- subprocess.run(["./magick.appimage","composite", "-geometry", "+" + str(x_offset) + "+" +str(y_offset), folder_path+"/"+"feather.png", folder_path+"/"+"alpha_compistion.png", folder_path+"/"+"alpha_compistion.png"])
-
-
-
-def make_transparent_border(original_image_cv, mask, ratio):
-
- if type(original_image_cv) is str:
- original_image_cv = cv2.imread(original_image_cv)
-
- transparent_bordered_image = cv2.cvtColor(original_image_cv, cv2.COLOR_RGB2RGBA)
-
- #객체의 긴 길이 구하기
-
- box_w, box_h = mask["box_w"], mask["box_h"]
- if box_w > box_h:
- longer = box_w
- else:
- longer = box_h
-
- #인물의 객체의 긴 길이가 55%, 1024*1024에서 55%(550픽셀)을 차지하도록 설정
- new_width, new_height = int(transparent_bordered_image.shape[1]*ratio*10/longer), int(transparent_bordered_image.shape[0]*ratio*10/longer)
- transparent_bordered_image = cv2.resize(transparent_bordered_image, (new_width, new_height))
-
- transparent_image = np.zeros((1024, 1024, 4), dtype=np.uint8)
- x_offset = int((transparent_image.shape[1] - transparent_bordered_image.shape[1]) / 2)
- y_offset = int((transparent_image.shape[0] - transparent_bordered_image.shape[0]) / 2)
-
- transparent_image[y_offset:y_offset + transparent_bordered_image.shape[0], x_offset:x_offset + transparent_bordered_image.shape[1]] = transparent_bordered_image
- transparent_bordered_image = transparent_image
-
- transparent_bordered_image_dictionary = {
- "transparent_bordered_image": transparent_bordered_image,
- "x_offset": x_offset,
- "y_offset": y_offset
- }
- return transparent_bordered_image_dictionary
-
diff --git "a/back-end/source_code/ssfshop/beanpole/\353\202\250\353\205\200\352\263\265\354\232\251 \353\262\240\354\235\264\354\247\201 \355\224\274\354\274\200 \355\213\260\354\205\224\354\270\240 - \353\270\224\353\236\231/DallE.png" "b/back-end/source_code/ssfshop/beanpole/\353\202\250\353\205\200\352\263\265\354\232\251 \353\262\240\354\235\264\354\247\201 \355\224\274\354\274\200 \355\213\260\354\205\224\354\270\240 - \353\270\224\353\236\231/DallE.png"
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diff --git "a/back-end/source_code/ssfshop/beanpole/\353\247\244\354\247\201 \354\215\250\354\273\244 \355\214\250\355\204\264 \354\212\254\353\246\274\355\225\217 \355\214\254\354\270\240 - \353\204\244\354\235\264\353\271\204/DallE.png" "b/back-end/source_code/ssfshop/beanpole/\353\247\244\354\247\201 \354\215\250\354\273\244 \355\214\250\355\204\264 \354\212\254\353\246\274\355\225\217 \355\214\254\354\270\240 - \353\204\244\354\235\264\353\271\204/DallE.png"
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diff --git "a/back-end/source_code/ssfshop/beanpole/\353\247\244\354\247\201 \354\215\250\354\273\244 \355\214\250\355\204\264 \354\212\254\353\246\274\355\225\217 \355\214\254\354\270\240 - \353\204\244\354\235\264\353\271\204/original.jpg" "b/back-end/source_code/ssfshop/beanpole/\353\247\244\354\247\201 \354\215\250\354\273\244 \355\214\250\355\204\264 \354\212\254\353\246\274\355\225\217 \355\214\254\354\270\240 - \353\204\244\354\235\264\353\271\204/original.jpg"
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diff --git a/back-end/source_code/temp.png b/back-end/source_code/temp.png
deleted file mode 100644
index 4555028d1edd84a5ed6d088e281cfdcbb27c3604..0000000000000000000000000000000000000000
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diff --git a/back-end/source_code/test.py b/back-end/source_code/test.py
new file mode 100644
index 0000000000000000000000000000000000000000..129bc28bc4c9a5af307ba919e0027f5ac50ad6eb
--- /dev/null
+++ b/back-end/source_code/test.py
@@ -0,0 +1,4 @@
+from modules import database
+
+databaseManager = database.DatabaseManager()
+
diff --git a/mask.png b/mask.png
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diff --git "a/back-end/source_code/ssfshop/beanpole/\353\202\250\353\205\200\352\263\265\354\232\251 \353\262\240\354\235\264\354\247\201 \355\224\274\354\274\200 \355\213\260\354\205\224\354\270\240 - \353\270\224\353\236\231/original.jpg" "b/ssfshop/beanpole/\353\202\250\353\205\200\352\263\265\354\232\251 \353\262\240\354\235\264\354\247\201 \355\224\274\354\274\200 \355\213\260\354\205\224\354\270\240 - \353\270\224\353\236\231/original.jpg"
similarity index 100%
rename from "back-end/source_code/ssfshop/beanpole/\353\202\250\353\205\200\352\263\265\354\232\251 \353\262\240\354\235\264\354\247\201 \355\224\274\354\274\200 \355\213\260\354\205\224\354\270\240 - \353\270\224\353\236\231/original.jpg"
rename to "ssfshop/beanpole/\353\202\250\353\205\200\352\263\265\354\232\251 \353\262\240\354\235\264\354\247\201 \355\224\274\354\274\200 \355\213\260\354\205\224\354\270\240 - \353\270\224\353\236\231/original.jpg"
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