FERMAT_TEST_REST_SERVER/GLASSES_AI_SERVER
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edit : 이미지생성 api 생성갯수 삭제, 이미지생성 api 데이터를 return해주는 api 추가, 입력이미지 입력받아 검색하는 api 추가

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김재웅
2025-08-07 16:54:46 +09:00
parent 5c20b9ccb5
commit 4ef360448a
5 changed files with 151 additions and 22 deletions
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18
main_rest/app/models.py
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@@ -587,9 +587,7 @@ class ImageGenerateReq(BaseModel):
"""
### [Request] image generate request
"""
prompt : str = Field(description='프롬프트', example='검은색 안경')
downloadCount : int = Field(1, description='이미지 생성 갯수', example=1)
prompt : str = Field(description='프롬프트', example='검은색 안경')
class BingCookieSetReq(BaseModel):
"""
@@ -615,6 +613,16 @@ class VectorImageSearchVitReq(BaseModel):
modelType : str = Field(VitModelType.l14, description='pretrained model 타입', example=VitModelType.l14)
indexType : str = Field(VitIndexType.l2, description='인덱스 타입', example=VitIndexType.l2)
searchNum : int = Field(4, description='검색결과 이미지 갯수', example=4)
class VectorImageSearchVitInputImgReq(BaseModel):
"""
### [Request] vector image search vit - input image
"""
inputImage : str = Field(description='base64 이미지', example='')
modelType : str = Field(VitModelType.l14, description='pretrained model 타입', example=VitModelType.l14)
indexType : str = Field(VitIndexType.l2, description='인덱스 타입', example=VitIndexType.l2)
searchNum : int = Field(4, description='검색결과 이미지 갯수', example=4)
class VectorImageSearchVitDataReq(VectorImageSearchVitReq):
@@ -623,6 +631,7 @@ class VectorImageSearchVitDataReq(VectorImageSearchVitReq):
"""
querySend: bool = Field(True, description='쿼리 이미지 전송 여부', example=True)
class VectorImageSearchVitReportReq(BaseModel):
"""
### [Request] vector image search vit request
@@ -631,6 +640,7 @@ class VectorImageSearchVitReportReq(BaseModel):
modelType : str = Field(VitModelType.l14, description='pretrained model 타입', example=VitModelType.l14)
indexType : str = Field(VitIndexType.l2, description='인덱스 타입', example=VitIndexType.l2)
class VectorImageResult(BaseModel):
image : str = Field("", description='이미지 데이터', example='')
percents: float = Field(0.0, description='percents 값', example='')
@@ -665,7 +675,7 @@ class ImageGenerateDataRes(ResponseBase):
"""
### image generate Data response
"""
imageData : int = Field(0, description='실제 이미지 생성 갯수', example=1)
imageData : str = Field('', description='이미지 데이터', example='')
@staticmethod
def set_error(error,img_data=''):

135
main_rest/app/routes/services.py
View File

@@ -17,7 +17,7 @@ from typing import Annotated, List
from main_rest.app.common import consts
from main_rest.app import models as M
from main_rest.app.utils.date_utils import D
from main_rest.app.utils.parsing_utils import image_to_base64_string
from main_rest.app.utils.parsing_utils import image_to_base64_string,save_base64_as_image_file
from custom_logger.main_log import main_logger as LOG
# from custom_apps.bingimagecreator.utils import DallEArgument,dalle3_generate_image
@@ -123,22 +123,16 @@ router = APIRouter(prefix="/services")
# LOG.error(traceback.format_exc())
# return response.set_error(e)
@router.post("/imageGenerate/imagen", summary="이미지 생성(AI) - imagen", response_model=M.ImageGenerateRes)
@router.post("/imageGenerate/imagen", summary="이미지 생성(AI) - imagen", response_model=M.ResponseBase)
async def imagen(request: Request, request_body_info: M.ImageGenerateReq):
"""
## 이미지 생성(AI) - imagen
> imagen AI를 이용하여 이미지 생성
"""
# imagen 사용중단 gemini로 변경
response = M.ImageGenerateRes()
response = M.ResponseBase()
try:
if not download_range(request_body_info.downloadCount):
raise Exception(f"downloadCount is 1~4 (current value = {request_body_info.downloadCount})")
# NOTE(JWKIM) : imagen 사용 중단
# img_length = imagen_generate_image(prompt=request_body_info.prompt,
# download_count=request_body_info.downloadCount
@@ -162,7 +156,44 @@ async def imagen(request: Request, request_body_info: M.ImageGenerateReq):
os.remove(temp_image_path)
del temp_image_path
return response.set_message(img_len=1)
return response.set_message()
except Exception as e:
LOG.error(traceback.format_exc())
# Clean up temporary files
if 'query_image_path' in locals():
if os.path.exists(query_image_path):
os.remove(query_image_path)
del query_image_path
return response.set_error(error=e)
@router.post("/imageGenerate/imagen/data", summary="이미지 생성(AI) - imagen(data)", response_model=M.ImageGenerateDataRes)
async def imagen_data(request: Request, request_body_info: M.ImageGenerateReq):
"""
## 이미지 생성(AI) - imagen
> imagen AI를 이용하여 이미지 데이터생성
"""
# imagen 사용중단 gemini로 변경
response = M.ImageGenerateDataRes()
try:
# NOTE(JWKIM) : imagen 사용 중단
# img_length = imagen_generate_image(prompt=request_body_info.prompt,
# download_count=request_body_info.downloadCount
# )
temp_image_path = gemini_image(request_body_info.prompt)
b64data = image_to_base64_string(temp_image_path)
# Clean up temporary files
if 'temp_image_path' in locals():
if os.path.exists(temp_image_path):
os.remove(temp_image_path)
del temp_image_path
return response.set_message(b64data)
except Exception as e:
LOG.error(traceback.format_exc())
@@ -231,9 +262,6 @@ async def vactor_vit(request: Request, request_body_info: M.VectorImageSearchVit
## 벡터 이미지 검색(clip-vit) - imagen
> imagen AI를 이용하여 이미지 생성 후 vector 검색 그후 결과 이미지 생성
### Requriements
> - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
### options
> - modelType -> b32,b16,l14,l14_336
> - indexType -> l2,cos
@@ -311,14 +339,11 @@ async def vactor_vit(request: Request, request_body_info: M.VectorImageSearchVit
return response.set_error(error=e)
@router.post("/vectorImageSearch/vit/imageGenerate/imagen/data", summary="벡터 이미지 검색(clip-vit) - imagen(data)", response_model=M.VectorImageSerachDataRes)
async def vactor_vit_report_data(request: Request, request_body_info: M.VectorImageSearchVitDataReq):
async def vactor_vit_data(request: Request, request_body_info: M.VectorImageSearchVitDataReq):
"""
## 벡터 이미지 검색(clip-vit) - imagen
> imagen AI를 이용하여 이미지 생성 후 vector 검색 그후 결과 이미지데이터 return
### Requriements
> - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
### options
> - modelType -> b32,b16,l14,l14_336
> - indexType -> l2,cos
@@ -389,6 +414,82 @@ async def vactor_vit_report_data(request: Request, request_body_info: M.VectorIm
del query_image_path
return response.set_error(error=e)
@router.post("/vectorImageSearch/vit/inputImage/data", summary="벡터 이미지 검색(clip-vit) - input image(data)", response_model=M.VectorImageSerachDataRes)
async def vactor_vit_input_img_data(request: Request, request_body_info: M.VectorImageSearchVitInputImgReq):
"""
## 벡터 이미지 검색(clip-vit) - inputimage
> 입력된 이미지로 vector 검색 그후 결과 이미지데이터 return
### Requriements
> - googlecli 설치(https://cloud.google.com/sdk/docs/install?hl=ko#linux)
### options
> - modelType -> b32,b16,l14,l14_336
> - indexType -> l2,cos
"""
response = M.VectorImageSerachDataRes()
query_image_data = ''
try:
if request_body_info.modelType not in [M.VitModelType.b32, M.VitModelType.b16, M.VitModelType.l14, M.VitModelType.l14_336]:
raise Exception(f"modelType is invalid (current value = {request_body_info.modelType})")
if request_body_info.indexType not in [M.VitIndexType.cos, M.VitIndexType.l2]:
raise Exception(f"indexType is invalid (current value = {request_body_info.indexType})")
query_image_path = os.path.join(TEMP_FOLDER, f'input_{D.date_file_name()}_query.png')
save_base64_as_image_file(request_body_info.inputImage ,query_image_path)
vector_request_data = {'query_image_path' : query_image_path,
'index_type' : request_body_info.indexType,
'model_type' : request_body_info.modelType,
'search_num' : request_body_info.searchNum}
vector_response = requests.post('http://localhost:51002/api/services/faiss/vector/search/vit', data=json.dumps(vector_request_data))
vector_response_dict = json.loads(vector_response.text)
if vector_response.status_code != 200:
raise Exception(f"response error: {vector_response_dict['error']}")
if vector_response_dict["error"] != None:
raise Exception(f"vector error: {vector_response_dict['error']}")
result_image_paths = vector_response_dict.get('img_list').get('result_image_paths')
result_percents = vector_response_dict.get('img_list').get('result_percents')
# 이미지 데이터 생성
vector_image_results = []
for img, percents in zip(result_image_paths, result_percents):
b64_data = image_to_base64_string(img)
float_percent = float(percents)
info = M.VectorImageResult(image=b64_data,percents=float_percent)
vector_image_results.append(info)
# Clean up temporary files
if 'query_image_path' in locals():
if os.path.exists(query_image_path):
os.remove(query_image_path)
del query_image_path
return response.set_message(vector_result=vector_image_results,query_img=query_image_data)
except Exception as e:
LOG.error(traceback.format_exc())
# Clean up temporary files
if 'query_image_path' in locals():
if os.path.exists(query_image_path):
os.remove(query_image_path)
del query_image_path
return response.set_error(error=e)
@router.post("/vectorImageSearch/vit/imageGenerate/imagen/report", summary="벡터 이미지 검색(clip-vit) - imagen, report 생성", response_model=M.ResponseBase)
async def vactor_vit_report(request: Request, request_body_info: M.VectorImageSearchVitReportReq):

13
main_rest/app/utils/parsing_utils.py
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@@ -58,4 +58,15 @@ def image_to_base64_string(image_path: str) -> str:
raise IOError(f"Error reading image file {image_path}: {e}")
except Exception as e:
# 그 외 예외 처리
raise Exception(f"An unexpected error occurred: {e}")
raise Exception(f"An unexpected error occurred: {e}")
def save_base64_as_image_file(base64_data: str, output_path: str):
"""
Base64 문자열을 디코딩하여 이미지 파일로 저장합니다.
"""
# Base64 문자열을 디코딩하여 이진 데이터로 변환합니다.
decoded_data = base64.b64decode(base64_data)
with open(output_path, "wb") as image_file:
image_file.write(decoded_data)

1
vector_rest/app/models.py
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@@ -611,6 +611,7 @@ class VactorSearchVitReq(BaseModel):
model_type : VitModelType = Field(VitModelType.l14, description='pretrained 모델 정보', example=VitModelType.l14)
search_num : int = Field(4, description='검색결과 이미지 갯수', example=4)
class VactorSearchVitRes(ResponseBase):
img_list : dict = Field({}, description='이미지 결과 리스트', example={})

6
vector_rest/app/routes/services.py
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@@ -55,6 +55,9 @@ async def vactor_search(request: Request, request_body_info: M.VactorSearchReq):
@router.post("/faiss/vector/search/vit/report", summary="vit search report", response_model=M.ResponseBase)
async def vactor_report_vit(request: Request, request_body_info: M.VactorSearchVitReportReq):
"""
이미지 경로를 입력받아 repport image 저장
"""
response = M.ResponseBase()
try:
if not os.path.exists(request_body_info.query_image_path):
@@ -74,6 +77,9 @@ async def vactor_report_vit(request: Request, request_body_info: M.VactorSearchV
@router.post("/faiss/vector/search/vit", summary="vit search", response_model=M.VactorSearchVitRes)
async def vactor_vit(request: Request, request_body_info: M.VactorSearchVitReq):
"""
이미지 경로 를 입력받아 vit 방식으로 검색
"""
response = M.VactorSearchVitRes()
try:
if not os.path.exists(request_body_info.query_image_path):