def generateTestData(pid, expid):
db = get_db()
#try:
dataloader = createDataLoader(db, pid, expid)
device = initDevice(db, pid, expid)
print(device)
print(dataloader)
imgpath = addImage(db, expid, "INPUTDATA")
print(imgpath)
# generateInputImageGrid(dataloader, imgpath, device)
#===============================================
# Use selected GAN image grid generate function
#===============================================
(ganDir, ganFile, ganClass) = getGANInfo(db, expid)
# import gan from gan file
#* my_module = importlib.import_module("GANEX.fastGAN.{}".format(ganFile))
#* gan = eval("my_module.{}(db, pid, expid)".format(ganClass))
gan = create_gan_object(db, pid, expid, ganDir, ganFile, ganClass)
# gan.setDevice()
# gan.prepareData()
gan.generate_input_image_grid(imgpath)
print("test data")
#return jsonify(imgpath=imgpath)
#except Exception as e:
# flash(e)
# img_path_list = getImagePaths(db, expid, "INPUTDATA")
# print("image path list:", img_path_list)
return jsonify(imgpath=imgpath)
def rqst_train_exp(pid, expid):
print("Training")
try:
db = get_db()
# status = getExpState(db, expid)
(ganDir, ganFile, ganClass) = getGANInfo(db, expid)
gan = create_gan_object(db, pid, expid, ganDir, ganFile, ganClass)
# gan.run()
x = threading.Thread(target=gan.run)
x.start()
setExpState(db, expid, "RETRAIN")
except Exception as e:
print(str(e))
def request_inference_generate(pid, expid, model_path):
print("Request received to make inference plot")
db = get_db()
(ganDir, ganFile, ganClass) = getGANInfo(db, expid)
# my_module = importlib.import_module("GANEX.fastGAN.{}".format(ganFile))
# gan = eval("my_module.{}(db, pid, expid)".format(ganClass))
gan = create_gan_object(db, pid, expid, ganDir, ganFile, ganClass)
gan.inference(model_path)
img_list = get_output_imgs(db, expid, "INFERENCED")
emit("inference-get-inferenced-imgs", img_list, namespace='/inference')
print(img_list)
def rqst_retrain_exp(pid, expid, model_path):
print("Re-Training")
print("Model path ", model_path)
try:
db = get_db()
# status = getExpState(db, expid)
(ganDir, ganFile, ganClass) = getGANInfo(db, expid)
gan = create_gan_object(db, pid, expid, ganDir, ganFile, ganClass)
# gan.rerun()
x = threading.Thread(target=gan.rerun, args=(model_path, ))
x.start()
setExpState(db, expid, "RETRAIN")
except Exception as e:
print(str(e))
def generate_sample_img(pid, expid):
db = get_db()
# add image path to db
# generateInputImageGrid(dataloader, imgpath, device)
#===============================================
# Use selected GAN image grid generate function
#===============================================
(ganDir, ganFile, ganClass) = getGANInfo(db, expid)
# import gan from gan file
#* my_module = importlib.import_module("GANEX.fastGAN.{}".format(ganFile))
#* gan = eval("my_module.{}(db, pid, expid)".format(ganClass))
gan = create_gan_object(db, pid, expid, ganDir, ganFile, ganClass)
#gan.setDevice()
#gan.prepareData()
imgpath = addImage(db, expid, "INPUTDATA")
gan.generate_input_image_grid(imgpath)
img_path_list = getImagePaths(db, expid, "INPUTDATA")
emit('data-get-img-paths', img_path_list, namespace='/data')
def runexp(pid, expid):
db = get_db()
status = getExpState(db, expid)
print("status:", status)
if status == None:
flash("status error")
if request.method == "POST":
print("POST request received")
if request.form["runexp_btn"] == "train":
try:
# get the GAN class
(ganDir, ganFile, ganClass) = getGANInfo(db, expid)
print("gan Dir=", ganDir)
print("gan file=", ganFile)
print("gan class=", ganClass)
# import gan from gan file
#* my_module = importlib.import_module("GANEX.fastGAN.{}".format(ganFile))
#* gan = eval("my_module.{}(db, pid, expid)".format(ganClass))
gan = create_gan_object(db, pid, expid, ganDir, ganFile,
ganClass)
# gan.run("BTN_TRAIN")
gan.run()
setExpState(db, expid, "RETRAIN")
#run(get_db(),pid, expid, status)
print("Training")
#setExpState(db, expid, "RETRAIN")
#status = getExpState(db, expid)
except Exception as e:
flash(str(e))
elif request.form["runexp_btn"] == "re-train":
try:
# get the GAN class
(ganDir, ganFile, ganClass) = getGANInfo(db, expid)
print("gan file=", ganFile)
print("gan class=", ganClass)
# import gan from gan file
#* my_module = importlib.import_module("GANEX.fastGAN.{}".format(ganFile))
#* gan = eval("my_module.{}(db, pid, expid)".format(ganClass))
gan = create_gan_object(db, pid, expid, ganDir, ganFile,
ganClass)
# * gan.run("BTN_RETRAIN")
gan.rerun()
setExpState(db, expid, "RETRAIN")
#run(get_db(),pid, expid, status)
print("Training")
#setExpState(db, expid, "RETRAIN")
#status = getExpState(db, expid)
except Exception as e:
flash(str(e))
print("Retraining")
elif request.form["runexp_btn"] == "reset":
print("Reset")
delTrainStats(db, expid)
setExpState(db, expid, "TRAIN")
status = getExpState(db, expid)
# reset default exp para
exp_para_list = get_default_exp_para(db, pid)
for exp_para in exp_para_list:
temp_dict = {exp_para["para_key"]: exp_para["para_value"]}
update_exp_info(db, expid, temp_dict)
print("exp para :", exp_para)
return render_template('run/runexp.html',
pid=pid,
expid=expid,
status=status)