- #1
falyusuf
- 35
- 3
Homework Statement: I am trying to write a Python code to do a project about smart parking system. I want to create a Mask RCNN model to detect the vehicles in the parking slots.
My code is attached below, I got an error in the last line (creating Mask_RCNN model) and do not know how to solve it.
Any help would be greatly appreciated.
Relevant Equations: -
I got the following error:
TypeError: 'module' object is not callable
My code is attached below, I got an error in the last line (creating Mask_RCNN model) and do not know how to solve it.
Any help would be greatly appreciated.
Relevant Equations: -
Python:
import subprocess
import keras.layers as KL
# Upgrade pip
import maskrcnn as maskrcnn
subprocess.check_call(['python', '-m', 'pip', 'install', '--upgrade', 'pip'])
# Install required libraries
subprocess.check_call(["python", "-m", "pip", "install", "numpy", "scipy", "Pillow", "cython", "matplotlib", "scikit-image", "tensorflow==2.5.0", "keras==2.4.3", "opencv-python", "h5py", "imgaug", "IPython"])
# Import required libraries
import os, cv2, keras
import numpy as np
import skimage.io
import matplotlib
import matplotlib.pyplot as plt
from keras import applications
from keras.preprocessing.image import ImageDataGenerator
from keras import optimizers
from keras.models import Sequential, Model
from keras.layers import Dropout, Flatten, Dense, GlobalAveragePooling2D
from keras import backend as k
from keras.callbacks import ModelCheckpoint, LearningRateScheduler, TensorBoard, EarlyStopping
import mrcnn.model as modellib
import mrcnn.config
class MaskRCNNConfig(mrcnn.config.Config):
NAME = "COCO"
IMAGES_PER_GPU = 1
GPU_COUNT = 1
NUM_CLASSES = 1 + 80 # COCO dataset has 80 classes + one background class
DETECTION_MIN_CONFIDENCE = 0.6
def get_car_boxes(boxes, class_ids):
car_boxes = []
for i, box in enumerate(boxes):
#detect cars and tracks only
if class_ids[i] in [3, 8, 6]:
car_boxes.append(box)
return np.array(car_boxes)
# Root directory of the project
ROOT_DIR = os.getcwd()
# Directory to save logs and trained model
#MODEL_DIR = os.path.join(ROOT_DIR, "logs")
# Local path to trained weights file
COCO_MODEL_PATH = os.path.join(ROOT_DIR, "mask_rcnn_coco.h5")
# Directory of images to run detection on
IMAGE_DIR = os.path.join(ROOT_DIR, "images")
# Create model object in inference mode.
model=maskrcnn(mode="inference", model_dir='mask_rcnn_coco.hy', config=MaskRCNNConfig())
I got the following error:
TypeError: 'module' object is not callable