Interactive_Visualization_Control_Understanding_ML_System/utils.py at main · felicialuo/Interactive_Visualization_Control_Understanding_ML_System · GitHub

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import cv2
import csv
import os


def readLabel2color():
    with open("../realtime_object_detection_w_depth/unique_label2color.csv", mode="r") as file:
        reader = csv.reader(file)
        label2color = {}
        next(reader)
        for row in reader:
            index, label, R, G, B = row
            label2color[label] = (  int(B), int(G), int(R))
    return label2color

def drawObjectDetection(obj_det_csv_path, color_frame, ifDepth):
    label2color = readLabel2color()

    with open(obj_det_csv_path, mode='r') as file:
        csv_reader = csv.reader(file)
        next(csv_reader)

        for row in csv_reader:
            label, confidence, left, top, right, bottom, center_dist = row
            confidence, left, top, right, bottom = float(confidence), int(left), int(top), int(right), int(bottom)
            center_dist = round(float(center_dist), 2)
            color = label2color[label]

            cv2.rectangle(color_frame, (left,top), (right,bottom), color, 1)
            label += f" {int(confidence * 100)}%"


            labelSize, baseLine = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
            top = max(top, labelSize[1])
            cv2.putText(color_frame, label,(left,top-5), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color, 1)
            if ifDepth:
                distance_string = str(center_dist) + " meter away"
                cv2.putText(color_frame,distance_string,(left,top+10), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color, 1)


def drawCLIP(csv_path, frame, color=(0,255,255)):
    height = 50
    cv2.putText(frame, "Per Second Activity Recognition:", (5,height), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color, 1),
    with open(csv_path, mode='r') as file:
        csv_reader = csv.reader(file)
        next(csv_reader)

        for row in csv_reader:
            height += 10
            label, confidence = row
            cv2.putText(frame, f"{label} {confidence}", (5,height), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color, 1)


def drawVCLIP(csv_path, frame, color=(255,255,255)):
    height = 120
    cv2.putText(frame, "Per Minute Activity Recognition:", (5,height), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color, 1)

    with open(csv_path, mode='r') as file:
        csv_reader = csv.reader(file)
        next(csv_reader)

        for row in csv_reader:
            height += 10
            label, confidence = row
            cv2.putText(frame, f"{label} {confidence}", (5,height), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color, 1)


def drawSKLTACT(csv_path, frame, color=(255,255,255)):
    height = 10
    cv2.putText(frame, "Skeleton-based Activity Recognition:", (5,height), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color, 1)

    # with open(csv_path, mode='r') as file:
    #     csv_reader = csv.reader(file)
    #     next(csv_reader)

    #     for row in csv_reader:
    #         height += 10
    #         label, confidence = row
    #         cv2.putText(frame, f"{label} {confidence}", (5,height), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color, 1)


def compile_knowledge_base(dataset_folder, header, DIR_IN, i_start, i_end):
    PATH_OUT = dataset_folder + header.replace(" ", "_") + ".csv"
    all_csv = sorted([f for f in os.listdir(DIR_IN)])

    with open(PATH_OUT, mode='w', newline='') as file:
        writer = csv.writer(file)
        # writer.writerow([header])
        for csv_path in all_csv[i_start : i_end]:
            to_write = [header]
            with open(os.path.join(DIR_IN, csv_path), mode='r') as label_file:
                reader  = csv.reader(label_file)
                next(reader)
                for row in reader:
                    to_write.extend(row[:2])
            # make sure all rows are same length
            if len(to_write) < 50: to_write += [" "] * (50 - len(to_write))
            writer.writerow([csv_path[:8].replace("_", ":")] + to_write)

    return PATH_OUT


def reinit_assistant(session_state, ifRGB, ifDepth, ifObjDet, ifPose, ifActRecog, timeframe_start, timeframe_end):
    if (session_state.ifRGB != ifRGB or session_state.ifDepth != ifDepth or session_state.ifObjDet != ifObjDet\
        or session_state.ifPose != ifPose or session_state.ifActRecog != ifActRecog\
            or session_state.timeframe_start != timeframe_start  or session_state.timeframe_end != timeframe_end):

        session_state.ifRGB = ifRGB
        session_state.ifDepth = ifDepth
        session_state.ifObjDet = ifObjDet
        session_state.ifPose = ifPose
        session_state.ifActRecog = ifActRecog
        session_state.timeframe_start = timeframe_start
        session_state.timeframe_end = timeframe_end

        print("===============REINIT ASSISTANT===============")
        return True