diff options
Diffstat (limited to 'backend')
-rw-r--r-- | backend/microservice/api/config.py | 2 | ||||
-rw-r--r-- | backend/microservice/api/controller.py | 16 | ||||
-rw-r--r-- | backend/microservice/api/newmlservice.py | 5 |
3 files changed, 14 insertions, 9 deletions
diff --git a/backend/microservice/api/config.py b/backend/microservice/api/config.py index 2b6fbe89..8fb088a7 100644 --- a/backend/microservice/api/config.py +++ b/backend/microservice/api/config.py @@ -1,2 +1,2 @@ api_url = "http://localhost:5283/api" - +hostIP = "127.0.0.1:5543"
\ No newline at end of file diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index 8e12c41d..d7564b70 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -9,7 +9,7 @@ import config app = flask.Flask(__name__) app.config["DEBUG"] = True -app.config["SERVER_NAME"] = "127.0.0.1:5543" +app.config["SERVER_NAME"] = config.hostIP class train_callback(tf.keras.callbacks.Callback): def __init__(self, x_test, y_test): @@ -33,19 +33,19 @@ def train(): paramsExperiment = json.loads(request.form["experiment"]) paramsDataset = json.loads(request.form["dataset"]) #dataset, paramsModel, paramsExperiment, callback) - result = newmlservice.train(data, paramsModel, paramsExperiment,paramsDataset, train_callback) + result = newmlservice.train(data, paramsModel, paramsExperiment, paramsDataset, train_callback) print(result) return jsonify(result) @app.route('/predict', methods = ['POST']) def predict(): - f = request.json['filepath'] - dataset = pd.read_csv(f) - m = request.json['modelpath'] - model = tf.keras.models.load_model(m) + h5 = request.files.get("h5file") + model = tf.keras.models.load_model(h5) + paramsExperiment = json.loads(request.form["experiment"]) + paramsPredictor = json.loads(request.form["predictor"]) print("********************************model loaded*******************************") - newmlservice.manageH5(dataset,request.json['model'],model) - return "done" + result = newmlservice.predict(paramsExperiment, paramsPredictor, model) + return result @app.route('/preprocess',methods=['POST']) def returnColumnsInfo(): diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py index ecadb0f4..74ad232e 100644 --- a/backend/microservice/api/newmlservice.py +++ b/backend/microservice/api/newmlservice.py @@ -432,6 +432,11 @@ def train(dataset, params, callback): micro_averaged_f1=metrics.f1_score(y_test, y_pred, average = 'micro') roc_auc_dict=roc_auc_score_multiclass(y_test, y_pred) ''' +def predict(experiment, predictor, model) { + #model.predict() + # ovo je pre bilo manageH5 + return "TODO" +} def manageH5(dataset,params,h5model): problem_type = params["type"] |