Inference on test images

[rabiyaabbasi]

Hi I have used detectron 2 for instance segmentation of my custom data. My model is trained and is saved as "model_final.pth". I have jupyter notebook to perform training. My question is how to reload the model in different notebook and run inference on test images. I have used the following code but its not doing anything except displaying the image without mask, prediction and bounding box. Can anyone tell me what I am doing wrong? When I run the same code in the jupyter notebook where I trained my model, it works perfectly fine but when I run it in different jupyter notebook, its not giving me desired results. Thanks alot.

`%cd detectron2
!python setup.py build develop

from detectron2.engine import DefaultTrainer
from detectron2.config import get_cfg
import detectron2
from detectron2.utils.logger import setup_logger
setup_logger()

import numpy as np
import os, json, cv2, random

from detectron2 import model_zoo
from detectron2.engine import DefaultPredictor
from detectron2.config import get_cfg
from detectron2.utils.visualizer import Visualizer
from detectron2.data import MetadataCatalog, DatasetCatalog
from detectron2.structures import BoxMode
import torch

import matplotlib.pyplot as plt
%matplotlib inline

def cv2_imshow(im):
im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
plt.figure(), plt.imshow(im), plt.axis('off');

cfg = get_cfg()

cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml"))
cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, "model_final.pth")
cfg.DATASETS.TEST = ("my_dataset_test", )
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.7 # set the testing threshold for this model
predictor = DefaultPredictor(cfg)
test_metadata = MetadataCatalog.get("my_dataset_test")

from detectron2.utils.visualizer import ColorMode

im = cv2.imread("Phase3-3 (18).jpg")
im=cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
outputs = predictor(im)
v = Visualizer(im[:, :, ::-1],
metadata=test_metadata,
scale=0.8
)
out = v.draw_instance_predictions(outputs["instances"].to("cpu"))
cv2_imshow(out.get_image()[:, :, ::-1])

`