output.txt

appuser@0350938812fa:/tmp/src$ python3 test.py
Failed to load OpenCL runtime
## PROPOSALS ##
Instances(num_instances=2000, image_height=573, image_width=687, fields=[proposal_boxes, objectness_logits])
## FIELDS ##
{'proposal_boxes': Boxes(tensor([[286.9893,  37.3016, 687.0000, 536.0049],
        [161.1793,  62.7907, 687.0000, 573.0000],
        [256.4062, 144.6316, 687.0000, 573.0000],
        ...,
        [464.0695, 306.8295, 477.6617, 346.7988],
        [288.0411, 148.8542, 340.1854, 304.7098],
        [472.3310, 230.6041, 499.8146, 254.9045]], device='cuda:0')), 'objectness_logits': tensor([ 6.8021,  6.4931,  6.4103,  ..., -2.8630, -2.8631, -2.8631],
       device='cuda:0')}

test.py

import os
import cv2 

from detectron2.config import get_cfg
from detectron2 import model_zoo
from detectron2.engine import DefaultPredictor
from detectron2.utils.visualizer import Visualizer, ColorMode
from detectron2.data import MetadataCatalog

classes = ["Blacky", "Niche"]

cfg = get_cfg()
cfg.merge_from_file(model_zoo.get_config_file("COCO-Detection/rpn_R_50_C4_1x.yaml"))
cfg.DATASETS.TEST = ("cats_val")
cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, "model_final_deepseek.pth")
cfg.MODEL.ROI_HEADS.NUM_CLASSES = 2
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.7

predictor = DefaultPredictor(cfg)

# Predict image
def test_image(image_path):
    image = cv2.imread(image_path)

    outputs = predictor(image)
    
    print("## PROPOSALS ##")
    print(outputs['proposals'])

    print("## FIELDS ##")
    print(outputs['proposals'].get_fields())