aidlab/AiDA_Python
6
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat design batch

Browse Source 
fix
This commit is contained in:
zhouchengrong
2024-09-12 10:06:25 +08:00
parent 44bb380944
commit 423ff8dd26
3 changed files with 160 additions and 46 deletions
Download Patch File Download Diff File Expand all files Collapse all files

41
app/api/api_design.py
View File

@@ -1,12 +1,14 @@
import json
import logging
import os
from fastapi import APIRouter, HTTPException
from fastapi import APIRouter, HTTPException, UploadFile, File, Form
from app.schemas.design import DesignModel, DesignProgressModel, ModelProgressModel
from app.schemas.design import DesignModel, DesignProgressModel, ModelProgressModel, DBGConfigModel
from app.schemas.response_template import ResponseModel
from app.service.design.model_process_service import model_transpose
from app.service.design.service import generate
from app.service.design.service_design_batch_generate import start_design_batch_generate
from app.service.design.utils.redis_utils import Redis
router = APIRouter()
@@ -238,3 +240,38 @@ def model_process(request_data: ModelProgressModel):
logger.warning(f"model_process Run Exception @@@@@@:{e}")
raise HTTPException(status_code=404, detail=str(e))
return ResponseModel(data=data)
# ##############################################################
@router.post("/design_batch_generate")
async def design(file: UploadFile = File(...),
tasks_id: str = Form(...),
user_id: str = Form(...),
priority: int = Form(...),
total: int = Form(...)
):
# file_content = await file.read()
dbg_config = DBGConfigModel(
tasks_id=tasks_id,
user_id=user_id,
priority=priority,
total=total
)
contents = await file.read()
file_name = file.filename
await save_request_file(contents, file_name)
return await start_design_batch_generate(dbg_config, contents)
async def save_request_file(contents, file_name):
# 创建保存文件的目录（如果不存在）
save_dir = os.path.join(os.getcwd(), "design_batch", "request_data")
if not os.path.exists(save_dir):
os.makedirs(save_dir)
# 处理文件
file_path = os.path.join(save_dir, file_name)
with open(file_path, "wb") as f:
f.write(contents)

51
app/schemas/design.py
View File

@@ -1,50 +1,6 @@
from pydantic import BaseModel
# class BodyPointModel(BaseModel):
# waistband_right: list[int]
# hand_point_right: list[int]
# waistband_left: list[int]
# hand_point_left: list[int]
# shoulder_left: list[int]
# shoulder_right: list[int]
#
#
# class BasicModel(BaseModel):
# body_point: BodyPointModel
# layer_order: bool
# scale_bag: float
# scale_earrings: float
# self_template: bool
# single_overall: str
# switch_category: str
# body_path: str
#
#
# class PrintModel(BaseModel):
# if_single: bool
# print_path_list: list[str]
#
#
# class ItemModel(BaseModel):
# color: str
# image_id: str
# offset: list[int]
# path: str
# print: PrintModel
# resize_scale: float
# type: str
#
#
# class CollocationModel(BaseModel):
# basic: BasicModel
# item: list[ItemModel]
#
#
# class DesignModel(BaseModel):
# object: list[CollocationModel]
# process_id: str
class DesignModel(BaseModel):
objects: list[dict]
process_id: str
@@ -56,3 +12,10 @@ class DesignProgressModel(BaseModel):
class ModelProgressModel(BaseModel):
model_path: str
class DBGConfigModel(BaseModel):
tasks_id: str
user_id: str
priority: int
total: int

114
app/service/design/service_design_batch_generate.py Normal file
View File

@@ -0,0 +1,114 @@
import json
import pika
from celery import Celery
from app.service.design.design_batch.items.item import process_layer, process_item, update_base_size_priority
from app.service.design.utils.synthesis_item import synthesis_single, synthesis
celery_app = Celery('clothes_generation', broker='amqp://guest:guest@localhost:5672//')
@celery_app.task
def design_batch_generate(design_objects, total_steps, task_id):
objects_response = []
for step, object in enumerate(design_objects):
basic = object['basic']
items_response = {'layers': []}
if basic['single_overall'] == "overall":
item_results = [process_item(item, basic) for item in object['items']]
layers = []
futures = []
body_size = None
for item in item_results:
futures = [process_layer(item, layers)]
for future in futures:
if future is not None:
body_size = future
layers = sorted(layers, key=lambda s: s.get("priority", float('inf')))
layers, new_size = update_base_size_priority(layers, body_size)
for lay in layers:
items_response['layers'].append({
'image_category': lay['name'],
'position': lay['position'],
'priority': lay.get("priority", None),
'resize_scale': lay['resize_scale'] if "resize_scale" in lay.keys() else None,
'image_size': lay['image'] if lay['image'] is None else lay['image'].size,
'gradient_string': lay['gradient_string'] if 'gradient_string' in lay.keys() else "",
'mask_url': lay['mask_url'],
'image_url': lay['image_url'] if 'image_url' in lay.keys() else None,
'pattern_image_url': lay['pattern_image_url'] if 'pattern_image_url' in lay.keys() else None,
# 'image': lay['image'],
# 'mask_image': lay['mask_image'],
})
items_response['synthesis_url'] = synthesis(layers, new_size, basic)
else:
item_results = process_item(object['items'][0], basic)
items_response['layers'].append({
'image_category': f"{item_results['name']}_front",
'image_size': item_results['back_image'].size if item_results['back_image'] else None,
'position': None,
'priority': 0,
'image_url': item_results['front_image_url'],
'mask_url': item_results['mask_url'],
"gradient_string": item_results['gradient_string'] if 'gradient_string' in item_results.keys() else "",
'pattern_image_url': item_results['pattern_image_url'] if 'pattern_image_url' in item_results.keys() else None,
})
items_response['layers'].append({
'image_category': f"{item_results['name']}_back",
'image_size': item_results['front_image'].size if item_results['front_image'] else None,
'position': None,
'priority': 0,
'image_url': item_results['back_image_url'],
'mask_url': item_results['mask_url'],
"gradient_string": item_results['gradient_string'] if 'gradient_string' in item_results.keys() else "",
'pattern_image_url': item_results['pattern_image_url'] if 'pattern_image_url' in item_results.keys() else None,
})
items_response['synthesis_url'] = synthesis_single(item_results['front_image'], item_results['back_image'])
objects_response.append(items_response)
publish_status(task_id, f"{step + 1}/{total_steps}", objects_response)
print(objects_response)
return objects_response
def publish_status(task_id, progress, result):
connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
channel = connection.channel()
channel.queue_declare(queue='DesignBatch', durable=True)
message = {'task_id': task_id, 'progress': progress, "result": result}
print(message)
channel.basic_publish(exchange='',
routing_key='DesignBatch',
body=json.dumps(message),
properties=pika.BasicProperties(
delivery_mode=2,
))
connection.close()
async def start_design_batch_generate(data, file):
generate_clothes_task = design_batch_generate.delay(json.loads(file.decode())['objects'], data.total, data.tasks_id)
print(generate_clothes_task)
publish_status(data.tasks_id, "0/100", "")
return {"task_id": data.tasks_id}
#
#
# if __name__ == '__main__':
# data = {"objects": [{"basic": {"body_point_test": {"waistband_right": [200, 241], "hand_point_right": [223, 297], "waistband_left": [112, 241], "hand_point_left": [92, 305], "shoulder_left": [99, 116], "shoulder_right": [215, 116]}, "layer_order": True, "scale_bag": 0.7, "scale_earrings": 0.16, "self_template": True, "single_overall": "overall", "switch_category": ""}, "items": [
# {"businessId": 270372, "color": "30 28 28", "image_id": 69780, "offset": [0, 0], "path": "aida-sys-image/images/female/trousers/0825000630.jpg", "seg_mask_url": "test/result.png",
# "print": {"element": {"element_angle_list": [], "element_path_list": [], "element_scale_list": [], "location": []}, "overall": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []}, "single": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []}}, "priority": 10, "resize_scale": [1.0, 1.0], "type": "Trousers"},
# {"businessId": 270373, "color": "30 28 28", "image_id": 98243, "offset": [0, 0], "path": "aida-sys-image/images/female/blouse/0902003811.jpg", "seg_mask_url": "test/result.png",
# "print": {"element": {"element_angle_list": [], "element_path_list": [], "element_scale_list": [], "location": []}, "overall": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []}, "single": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []}}, "priority": 11, "resize_scale": [1.0, 1.0], "type": "Blouse"},
# {"businessId": 270374, "color": "172 68 68", "image_id": 98244, "offset": [0, 0], "path": "aida-sys-image/images/female/outwear/0825000410.jpg", "seg_mask_url": "test/result.png",
# "print": {"element": {"element_angle_list": [], "element_path_list": [], "element_scale_list": [], "location": []}, "overall": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []}, "single": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []}}, "priority": 12, "resize_scale": [1.0, 1.0], "type": "Outwear"},
# {"body_path": "aida-sys-image/models/female/5bdfe7ca-64eb-44e4-b03d-8e517520c795.png", "image_id": 96090, "type": "Body"}]}], "process_id": "83"}
# total_steps = 1
# task_id = 1
# design_batch_generate(data['objects'], total_steps, task_id)
# # publish_status(task_id="0/100", progress=100)