def do_search_api():
input_args = reqparse.RequestParser(). \
add_argument("Table", type=str). \
add_argument("Num", type=int, default=1). \
add_argument("Caption", type=str). \
parse_args()
captions = input_args['Caption']
print(captions)
table_name = input_args['Table']
top_k = input_args['Num']
if not table_name:
table_name = DEFAULT_TABLE
print(table_name)
if not captions:
return "no captions", 400
if captions:
# filename = secure_filename(file.filename)
# file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
# file.save(file_path)
res_id, res_distance = do_search(table_name, captions, top_k, model, args)
if isinstance(res_id, str):
return res_id
# res_img = [request.url_root + "data/" + x for x in res_id]
# res = dict(zip(res_img, res_distance))
# res = sorted(res.items(), key=lambda item: item[1])
# return jsonify(res), 200
return "not found", 400
def do_search_api():
args = reqparse.RequestParser(). \
add_argument("Molecular", type=str). \
add_argument("Type", type=str, default='similarity'). \
add_argument("Cid", type=int). \
parse_args()
molecular_name = args['Molecular']
search_type = args['Type']
cid_num = args['Cid']
if search_type == 'similarity':
table_name = SIM_TABLE
elif search_type == 'substructure':
table_name = SUB_TABLE
elif search_type == 'superstructure':
table_name = SUPER_TABLE
top_k = NUM
if cid_num:
from pubchempy import get_compounds, Compound
comp = Compound.from_cid(cid_num)
molecular_name = comp.isomeric_smiles
if not molecular_name:
return "no molecular"
if molecular_name:
try:
res_smi = do_search(table_name, molecular_name, top_k)
except:
return "There has no results, please input the correct molecular and ensure the table has data."
re = {}
re["Smiles"] = res_smi
return jsonify(re), 200
return "not found", 400
def do_search_api():
args = reqparse.RequestParser(). \
add_argument("Table", type=str). \
add_argument("Num", type=int, default=1). \
parse_args()
table_name = args['Table']
if not table_name:
table_name = DEFAULT_TABLE
top_k = args['Num']
file = request.files.get('file', "")
if not file:
return "no file data", 400
if not file.name:
return "need file name", 400
if file:
filename = secure_filename(file.filename)
file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
file.save(file_path)
res_id, res_distance = do_search(table_name, file_path, top_k, model,
graph, sess)
if isinstance(res_id, str):
return res_id
res_img = [request.url_root + "data/" + x for x in res_id]
res = dict(zip(res_img, res_distance))
res = sorted(res.items(), key=lambda item: item[1])
print(jsonify(res))
return jsonify(res), 200
return "not found", 400
def do_search_images_api():
args = reqparse.RequestParser(). \
add_argument('Id', type=str). \
add_argument('Table', type=str). \
add_argument('Image', type=str). \
add_argument('FileId', type=str). \
add_argument('FileImage', type=str). \
parse_args()
file_id = request.files.get('FileId', "")
file_image = request.files.get('FileImage', "")
table_name = args['Table']
if file_id:
ids = str(file_id.read().decode("utf-8")).strip().split(",")
ids = ids[:-1]
else:
ids = args['Id'].split(",")
if file_image:
image = str(file_image.read().decode("utf-8")).strip().split(",")
image = image[:-1]
else:
image = args['Image'].split(",")
try:
index_client, conn, cursor = init_conn()
result, distance = do_search(index_client, conn, cursor, img_to_vec,
image, table_name)
print("----------------search_results:", result, distance)
# Python 字典类型转换为 JSON 对象
result_dic = {"code": 0, "msg": "success"}
data = []
for i in range(len(ids)):
id_dis = []
for j in range(len(result[i])):
id_sim = {"id": result[i][j], "similarity": distance[i][j]}
id_dis.append(id_sim)
re_sim = {"id": ids[i], "similarImages": id_dis}
data.append(re_sim)
result_dic["data"] = data
# with open("results_0630.txt","w") as f:
# f.write(str(ids).replace('[','').replace(']','').replace('\'','').replace('‘','')+'\n')
# f.write("\n")
# for i in result:
# f.write(str(i).replace('[','').replace(']','').replace('\'','').replace('‘','')+'\n')
# return "{0},{1}".format(ids, result), 200
return result_dic, 200
except Exception as e:
write_log(e, 1)
return "Error with {}".format(e), 400
def do_search_images_api(request: Request, search_id: list, table_name: str=None):
try:
index_client, conn, cursor = init_conn()
host = request.headers['host']
img_list = get_img_list()
list_id = do_search(index_client, conn, cursor, img_list, search_id, table_name)
# print("--------", list_id)
info = get_list_info(conn, cursor, table_name, host, list_id)
return info, 200
except Exception as e:
logging.error(e)
return "Error with {}".format(e), 400
async def do_search_images_api(request: Request, Text: str, Image: UploadFile = File(...), table_name: str=None):
try:
index_client, conn, cursor = init_conn()
host = request.headers['host']
content = await Image.read()
with open ("./test/test.png" ,'wb') as f :
f.write(content)
Image ="./test/test.png"
img_list = get_img_list()
list_id = do_search(index_client, conn, cursor ,Text, Image,table_name,img_list,host)
print("--------", list_id)
return list_id, 200
except Exception as e:
logging.error(e)
print(traceback.format_exc())
def do_search_api():
args = reqparse.RequestParser(). \
add_argument("Table", type=str). \
add_argument("Num", type=int, default=1). \
add_argument("Molecular", type=str). \
parse_args()
table_name = args['Table']
if not table_name:
table_name = DEFAULT_TABLE
top_k = args['Num']
molecular_name = args['Molecular']
if not molecular_name:
return "no molecular"
if molecular_name:
try:
shutil.rmtree(UPLOAD_PATH)
os.mkdir(UPLOAD_PATH)
except:
print("cannot remove:", UPLOAD_PATH)
try:
res_smi, res_distance, ids = do_search(table_name, molecular_name,
top_k)
except:
return "There has no results, please input the correct molecular and ensure the table has data."
res_mol = []
for i in range(len(res_smi)):
mol = Chem.MolFromSmiles(res_smi[i])
res_mol.append(mol)
print("res_mol:", len(res_mol))
re = {}
for i in range(len(res_smi)):
times = int(time.time())
sub_res_mol = [res_mol[i]]
sub_img = Draw.MolsToGridImage(sub_res_mol,
molsPerRow=1,
subImgSize=(500, 500))
sub_img.save(UPLOAD_PATH + "/similarities_results_" + str(ids[i]) +
"_" + str(times) + ".png")
res_img = request.url_root + "data/similarities_results_" + str(
ids[i]) + "_" + str(times) + ".png"
re[res_img] = [res_smi[i], res_distance[i]]
# img = Draw.MolsToGridImage(res_mol, molsPerRow=1, subImgSize=(500, 500),legends=["%s - %s" % (res_smi[x] , str(res_distance[x])) for x in range(len(res_mol))])
return jsonify(re), 200
return "not found", 400
def do_search_api():
args = reqparse.RequestParser(). \
add_argument("Table", type=str). \
add_argument("Num", type=int, default=1). \
parse_args()
table_name = args['Table']
if not table_name:
table_name = DEFAULT_TABLE
top_k = args['Num']
file = request.files.get('file', "")
if not file:
return "no file data", 400
if not file.name:
return "need file name", 400
if file:
filename = secure_filename(file.filename)
img_path = app.config['UPLOAD_FOLDER']+'/'+filename.split('.')[0]
if not os.path.exists(img_path):
os.mkdir(img_path)
file_path = os.path.join(img_path, filename)
file.save(file_path)
res_id,res_distance = do_search(image_encoder,table_name, img_path, top_k)
# print(res_id,res_distance)
# if isinstance(res_id, str):
# return res_id
res ={}
for img, dis in zip(res_id,res_distance):
# print("[[[[[[[[[[[[[[", img, dis)
key_img = request.url_root +"data/" + img
if key_img not in res.keys() or res[key_img] > dis:
res[key_img] = dis
#print("dic res:", res)
# res = dict(zip(res_img,res_distance))
#res = [list(g)[0] for k, g in groupby(sorted(res), key=itemgetter(0))]
# print(",,,,,,,",res)
res = sorted(res.items(),key=lambda item:item[1])
# myslice = slice(top_k)
# res=res[myslice]
return jsonify(res), 200
return "not found", 400
def do_search_api():
file_img = request.files.get('img', "")
file_video = request.files.get('video', None)
file_audio = request.files.get('audio', None)
ids = '{0:%Y%m%d%H%M%S%f}'.format(datetime.datetime.now())
status = {'status': 'faile', 'message': 'no file data'}
if file_video:
filename = secure_filename(file_video.filename)
file_path = os.path.join(app.config['DATA_FOLDER'], filename)
file_video.save(file_path)
video = VideoFileClip(file_path)
audio = video.audio
voc_path = os.path.join(app.config['DATA_FOLDER'], ids[:-1] + '.wav')
audio.write_audiofile(voc_path)
elif file_audio:
voc_path = os.path.join(app.config['DATA_FOLDER'], ids[:-1] + '.wav')
file_audio.save(voc_path)
else:
return jsonify(status), 200
if file_img:
img_path = os.path.join(app.config['DATA_FOLDER'], ids + '.png')
file_img.save(img_path)
try:
status = do_search(img_path, voc_path)
status[1] = request.url_root + "data/" + str(status[1]) + '.png'
except:
status = {
'status': 'faile',
'message': 'please confirm only one face in camera'
}
return jsonify(status), 200
finally:
os.remove(img_path)
os.remove(voc_path)
return "{}".format(status), 200
else:
return jsonify(status), 200
if not captions:
return "no captions", 400
if captions:
# filename = secure_filename(file.filename)
# file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
# file.save(file_path)
res_id, res_distance = do_search(table_name, captions, top_k, model, args)
if isinstance(res_id, str):
return res_id
# res_img = [request.url_root + "data/" + x for x in res_id]
# res = dict(zip(res_img, res_distance))
# res = sorted(res.items(), key=lambda item: item[1])
# return jsonify(res), 200
return "not found", 400
if __name__ == "__main__":
global args
global test_loader
global test_transform
args = config()
test_transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
])
test_loader = data_config(args.image_dir, args.anno_dir, 64, 'test', args.max_length, test_transform)
load_model()
# do_train('test02', test_loader, model, args)
captions = 'The man is wearing a blue and white striped tank top and green pants. He has pink headphones around his neck.'
do_search('test02', captions, 10, model, args)
app.run(host="192.168.1.85", port='5001')