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feat 测试批量上传图片

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fix
This commit is contained in:
zhouchengrong
2024-07-19 15:10:28 +08:00
parent b92b1f7d6e
commit ed908d0472
13 changed files with 160 additions and 48 deletions
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1
.gitignore vendored
View File

@@ -120,6 +120,7 @@ dmypy.json
#runtime produce
test
seg_cache
logs
seg_result/
seg_result

17
app/api/api_design.py
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@@ -136,13 +136,16 @@ def design(request_data: DesignModel):
"process_id": "89"
}
"""
try:
logger.info(f"design request item is : @@@@@@:{json.dumps(request_data.dict())}")
data = generate(request_data=request_data)
logger.info(f"design response @@@@@@:{json.dumps(data)}")
except Exception as e:
logger.warning(f"design Run Exception @@@@@@:{e}")
raise HTTPException(status_code=404, detail=str(e))
logger.info(f"design request item is : @@@@@@:{json.dumps(request_data.dict())}")
data = generate(request_data=request_data)
logger.info(f"design response @@@@@@:{json.dumps(data)}")
# try:
# logger.info(f"design request item is : @@@@@@:{json.dumps(request_data.dict())}")
# data = generate(request_data=request_data)
# logger.info(f"design response @@@@@@:{json.dumps(data)}")
# except Exception as e:
# logger.warning(f"design Run Exception @@@@@@:{e}")
# raise HTTPException(status_code=404, detail=str(e))
return ResponseModel(data=data)

4
app/core/config.py
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@@ -24,11 +24,11 @@ DEBUG = False
if DEBUG:
LOGS_PATH = "logs/"
CATEGORY_PATH = "service/attribute/config/descriptor/category/category_dis.csv"
# FACE_CLASSIFIER = "service/generate_image/utils/haarcascade_frontalface_alt.xml"
SEG_CACHE_PATH = "../seg_cache/"
else:
LOGS_PATH = "app/logs/"
CATEGORY_PATH = "app/service/attribute/config/descriptor/category/category_dis.csv"
# FACE_CLASSIFIER = 'app/service/generate_image/utils/haarcascade_frontalface_alt.xml'
SEG_CACHE_PATH = "/seg_cache/"
# RABBITMQ_ENV = "" # 生产环境
RABBITMQ_ENV = "-dev" # 开发环境

5
app/service/design/items/clothing.py
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@@ -37,7 +37,8 @@ class Clothing(object):
resize_scale=self.result["resize_scale"],
mask=cv2.resize(self.result['mask'], self.result["front_image"].size),
gradient_string=self.result['gradient_string'] if 'gradient_string' in self.result.keys() else "",
pattern_image_url=self.result['pattern_image_url']
pattern_image_url=self.result['pattern_image_url'],
pattern_image=self.result['pattern_image']
)
layer.insert(front_layer)
@@ -54,7 +55,7 @@ class Clothing(object):
resize_scale=self.result["resize_scale"],
mask=cv2.resize(self.result['mask'], self.result["front_image"].size),
gradient_string=self.result['gradient_string'] if 'gradient_string' in self.result.keys() else "",
pattern_image_url=self.result['pattern_image_url']
pattern_image_url=self.result['pattern_image_url'],
)
layer.insert(back_layer)

3
app/service/design/items/pipelines/keypoints.py
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@@ -5,6 +5,7 @@ import numpy as np
from pymilvus import MilvusClient
from app.core.config import *
from app.service.utils.decorator import RunTime, ClassCallRunTime
from ..builder import PIPELINES
from ...utils.design_ensemble import get_keypoint_result
@@ -27,7 +28,7 @@ class KeypointDetection(object):
# self.client.close()
# print(f"client close time : {time.time() - start_time}")
# @ RunTime
@ ClassCallRunTime
def __call__(self, result):
# logging.info("KeypointDetection run ")
if result['name'] in ['blouse', 'skirt', 'dress', 'outwear', 'trousers', 'tops', 'bottoms']: # 查询是否有数据 且类别相同 相同则直接读 不同则推理后更新

2
app/service/design/items/pipelines/loading.py
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@@ -1,5 +1,6 @@
import cv2
from app.service.utils.decorator import RunTime, ClassCallRunTime
from app.service.utils.oss_client import oss_get_image
from ..builder import PIPELINES
@@ -12,6 +13,7 @@ class LoadImageFromFile(object):
self.print_dict = print_dict
# self.minio_client = Minio(f"{MINIO_URL}", access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
@ClassCallRunTime
def __call__(self, result):
result['image'], result['pre_mask'] = self.read_image(self.path)
result['gray'] = cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY)

6
app/service/design/items/pipelines/painting.py
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@@ -4,6 +4,7 @@ import cv2
import numpy as np
from PIL import Image
from app.service.utils.decorator import RunTime, ClassCallRunTime
from app.service.utils.oss_client import oss_get_image
from ..builder import PIPELINES
@@ -13,7 +14,7 @@ class Painting(object):
def __init__(self, painting_flag=True):
self.painting_flag = painting_flag
# @ RunTime
@ClassCallRunTime
def __call__(self, result):
if result['name'] not in ['hairstyle', 'earring'] and self.painting_flag and result['color'] != 'none':
dim_image_h, dim_image_w = result['image'].shape[0:2]
@@ -86,7 +87,7 @@ class PrintPainting(object):
def __init__(self, print_flag=True):
self.print_flag = print_flag
# @ RunTime
@ClassCallRunTime
def __call__(self, result):
single_print = result['print']['single']
overall_print = result['print']['overall']
@@ -236,7 +237,6 @@ class PrintPainting(object):
print_background = cv2.cvtColor(np.array(source_image_pil), cv2.COLOR_RGBA2BGR)
mask_background = cv2.cvtColor(np.array(source_image_pil_mask), cv2.COLOR_RGBA2BGR)
print(1)
else:
mask = self.get_mask_inv(image)
mask = np.expand_dims(mask, axis=2)

3
app/service/design/items/pipelines/scale.py
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@@ -2,6 +2,7 @@ import math
import cv2
from app.service.utils.decorator import ClassCallRunTime
from ..builder import PIPELINES
@@ -10,7 +11,7 @@ class Scaling(object):
def __init__(self):
pass
# @ RunTime
@ClassCallRunTime
def __call__(self, result):
if result['keypoint'] in ['waistband', 'shoulder', 'head_point']:
# milvus_db_keypoint_cache

34
app/service/design/items/pipelines/segmentation.py
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@@ -1,3 +1,9 @@
import os
import numpy as np
from app.core.config import SEG_CACHE_PATH
from app.service.utils.decorator import ClassCallRunTime
from ..builder import PIPELINES
from ...utils.design_ensemble import get_seg_result
@@ -9,6 +15,32 @@ class Segmentation(object):
self.device = device
self.debug = debug
@ClassCallRunTime
def __call__(self, result):
result['seg_result'] = get_seg_result(result["image_id"], result['image'])
_, seg_result = self.load_seg_result(result["image_id"])
if not _:
result['seg_result'] = get_seg_result(result["image_id"], result['image'])
self.save_seg_result(result['seg_result'][0], result['image_id'])
return result
@staticmethod
def save_seg_result(seg_result, image_id):
file_path = f"{SEG_CACHE_PATH}{image_id}.npy"
try:
np.save(file_path, seg_result)
print("保存成功", os.path.abspath(file_path))
except Exception as e:
print(f"保存失败: {e}")
@staticmethod
def load_seg_result(image_id):
file_path = f"{SEG_CACHE_PATH}{image_id}.npy"
try:
seg_result = np.load(file_path)
return True, seg_result
except FileNotFoundError:
print("文件不存在")
return False, None
except Exception as e:
print(f"加载失败: {e}")
return False, None

4
app/service/design/items/pipelines/split.py
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@@ -5,6 +5,7 @@ import numpy as np
from PIL import Image
from cv2 import cvtColor, COLOR_BGR2RGBA
from app.service.utils.decorator import ClassCallRunTime
from app.service.utils.generate_uuid import generate_uuid
from ..builder import PIPELINES
from ...utils.conversion_image import rgb_to_rgba
@@ -17,6 +18,7 @@ class Split(object):
Split image into front and back layer according to the segmentation result
"""
@ClassCallRunTime
# KNet
def __call__(self, result):
try:
@@ -66,7 +68,7 @@ class Split(object):
# 创建中间图层
result_pattern_image_rgba = rgb_to_rgba(result['pattern_image'], result['mask'])
result_pattern_image_pil = Image.fromarray(cvtColor(result_pattern_image_rgba, COLOR_BGR2RGBA))
_, result['pattern_image_url'], _ = upload_png_mask(result_pattern_image_pil, f'{generate_uuid()}')
result['pattern'], result['pattern_image_url'], _ = upload_png_mask(result_pattern_image_pil, f'{generate_uuid()}')
return result
except Exception as e:
logging.warning(f"split runtime exception : {e} image_id : {result['image_id']}")

54
app/service/design/service.py
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@@ -1,4 +1,8 @@
import concurrent.futures
import io
import cv2
from PIL import Image
from app.core.config import PRIORITY_DICT
from app.service.design.core.layer import Layer
@@ -6,6 +10,7 @@ from app.service.design.items import build_item
from app.service.design.utils.redis_utils import Redis
from app.service.design.utils.synthesis_item import synthesis, synthesis_single
from app.service.utils.decorator import RunTime
from app.service.utils.oss_client import oss_upload_image
def process_item(item, layers):
@@ -43,6 +48,7 @@ def final_progress(process_id):
@RunTime
def generate(request_data):
return_response = {}
return_png_mask = []
request_data = request_data.dict()
assert "process_id" in request_data.keys(), "Need process_id parameters"
@@ -55,14 +61,15 @@ def generate(request_data):
# 获取处理结果
for future in concurrent.futures.as_completed(futures):
obj = futures[future]
result = future.result()
return_response[obj] = result
return_response[obj] = future.result()[0]
return_png_mask.extend(future.result()[1])
final_progress(process_id)
upload_results = process_images(return_png_mask)
return return_response
def process_object(cfg, process_id, total):
uploaded_images = []
basic_info = cfg.get('basic')
items_response = {
'layers': []
@@ -83,6 +90,15 @@ def process_object(cfg, process_id, total):
layers = sorted(layers.layer, key=lambda s: s.get("priority", float('inf')))
else:
layers = sorted(layers.layer, key=lambda x: PRIORITY_DICT.get(x['name'], float('inf')))
# 上传所有图片
for layer in layers:
if 'image' in layer.keys() and layer['image'] is not None:
uploaded_images.append({'image_obj': layer['image'], 'image_url': layer['image_url']})
if 'pattern_image' in layer.keys() and layer['pattern_image'] is not None:
uploaded_images.append({'image_obj': layer['pattern_image'], 'image_url': layer['pattern_image_url']})
if 'mask' in layer.keys() and layer['mask'] is not None and layer['mask_url'] is not None:
uploaded_images.append({'image_obj': layer['mask'], 'image_url': layer['mask_url']})
# 合成
items_response['synthesis_url'] = synthesis(layers, body_size)
@@ -131,4 +147,34 @@ def process_object(cfg, process_id, total):
items_response['synthesis_url'] = synthesis_single(item.result['front_image'], item.result['back_image'])
break
update_progress(process_id, total)
return items_response
return items_response, uploaded_images
@RunTime
def process_images(images):
with concurrent.futures.ThreadPoolExecutor() as executor:
results = list(executor.map(upload_images, images))
# results = []
# for image in images:
# results.append(upload_images(image))
return results
@RunTime
def upload_images(image_obj):
bucket_name = image_obj['image_url'].split("/", 1)[0]
object_name = image_obj['image_url'].split("/", 1)[1]
if isinstance(image_obj['image_obj'], Image.Image):
image_data = io.BytesIO()
image_obj['image_obj'].save(image_data, format='PNG')
image_data.seek(0)
image_bytes = image_data.read()
req = oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
return image_obj['image_url']
else:
mask_inverted = cv2.bitwise_not(image_obj['image_obj'])
# 将掩模的3通道转换为4通道，白色部分不透明，黑色部分透明
rgba_image = cv2.cvtColor(mask_inverted, cv2.COLOR_BGR2BGRA)
rgba_image[rgba_image[:, :, 0] == 0] = [0, 0, 0, 0]
req = oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=cv2.imencode('.png', rgba_image)[1])
return image_obj['image_url']

60
app/service/design/utils/upload_image.py
View File

@@ -13,33 +13,43 @@ import logging
import cv2
from app.core.config import *
from app.service.utils.decorator import RunTime
from app.service.utils.oss_client import oss_upload_image
# @RunTime
def upload_png_mask(front_image, object_name, mask=None):
try:
mask_url = None
if mask is not None:
mask_inverted = cv2.bitwise_not(mask)
# 将掩模的3通道转换为4通道，白色部分不透明，黑色部分透明
rgba_image = cv2.cvtColor(mask_inverted, cv2.COLOR_BGR2BGRA)
rgba_image[rgba_image[:, :, 0] == 0] = [0, 0, 0, 0]
# image_bytes = io.BytesIO()
# image_bytes.write(cv2.imencode('.png', rgba_image)[1].tobytes())
# image_bytes.seek(0)
# mask_url = f"{AIDA_CLOTHING}/{minio_client.put_object('aida-clothing', f'mask/mask_{object_name}.png', image_bytes, len(image_bytes.getvalue()), content_type='image/png').object_name}"
# oss upload ####################
req = oss_upload_image(bucket=AIDA_CLOTHING, object_name=f"mask/mask_{object_name}.png", image_bytes=cv2.imencode('.png', rgba_image)[1])
mask_url = f"{AIDA_CLOTHING}/mask/mask_{object_name}.png"
# def upload_png_mask(front_image, object_name, mask=None):
# try:
# mask_url = None
# if mask is not None:
# mask_inverted = cv2.bitwise_not(mask)
# # 将掩模的3通道转换为4通道，白色部分不透明，黑色部分透明
# rgba_image = cv2.cvtColor(mask_inverted, cv2.COLOR_BGR2BGRA)
# rgba_image[rgba_image[:, :, 0] == 0] = [0, 0, 0, 0]
# # image_bytes = io.BytesIO()
# # image_bytes.write(cv2.imencode('.png', rgba_image)[1].tobytes())
# # image_bytes.seek(0)
# # mask_url = f"{AIDA_CLOTHING}/{minio_client.put_object('aida-clothing', f'mask/mask_{object_name}.png', image_bytes, len(image_bytes.getvalue()), content_type='image/png').object_name}"
# # oss upload ####################
# req = oss_upload_image(bucket=AIDA_CLOTHING, object_name=f"mask/mask_{object_name}.png", image_bytes=cv2.imencode('.png', rgba_image)[1])
# mask_url = f"{AIDA_CLOTHING}/mask/mask_{object_name}.png"
#
# image_data = io.BytesIO()
# front_image.save(image_data, format='PNG')
# image_data.seek(0)
# image_bytes = image_data.read()
# # image_url = f"{AIDA_CLOTHING}/{minio_client.put_object('aida-clothing', f'image/image_{object_name}.png', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"
# req = oss_upload_image(bucket=AIDA_CLOTHING, object_name=f"image/image_{object_name}.png", image_bytes=image_bytes)
# image_url = f"{AIDA_CLOTHING}/image/image_{object_name}.png"
# return front_image, image_url, mask_url
# except Exception as e:
# logging.warning(f"upload_png_mask runtime exception : {e}")
image_data = io.BytesIO()
front_image.save(image_data, format='PNG')
image_data.seek(0)
image_bytes = image_data.read()
# image_url = f"{AIDA_CLOTHING}/{minio_client.put_object('aida-clothing', f'image/image_{object_name}.png', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"
req = oss_upload_image(bucket=AIDA_CLOTHING, object_name=f"image/image_{object_name}.png", image_bytes=image_bytes)
image_url = f"{AIDA_CLOTHING}/image/image_{object_name}.png"
return front_image, image_url, mask_url
except Exception as e:
logging.warning(f"upload_png_mask runtime exception : {e}")
@RunTime
def upload_png_mask(front_image, object_name, mask=None):
mask_url = None
if mask is not None:
mask_url = f"{AIDA_CLOTHING}/mask/mask_{object_name}.png"
image_url = f"{AIDA_CLOTHING}/image/image_{object_name}.png"
return front_image, image_url, mask_url

15
app/service/utils/decorator.py
View File

@@ -1,5 +1,5 @@
import time
import logging
import time
def RunTime(func):
@@ -12,3 +12,16 @@ def RunTime(func):
return res
return wrapper
def ClassCallRunTime(func):
def wrapper(*args, **kwargs):
start_time = time.time()
result = func(*args, **kwargs)
end_time = time.time()
execution_time = end_time - start_time
class_name = args[0].__class__.__name__ # 获取类名
print(f"class name: {class_name} , run time is : {execution_time} s")
return result
return wrapper