from model import model
import cv2
image_path = '/content/images/126_0_1280.tiff'
predictor = model()
predictor.load('/content')
img = cv2.imread(image_path, -1)
print(img.shape)
res = predictor.predict(img, None)
print(res)
I used this code you mentioned to get results. However, I would like to know to how to overlay these results on images and see as oriented bboxes overlayed on images.(can you provide a code snippet for that)
Posted by: prak @ April 18, 2023, 9:07 p.m.Hi,
I recommend reviewing the implementation of the "Frame and annotations display" section in the EDA notebook.
Neta,
MAFAT Challenge Team
'Second, you can find a prediction sample for one frame at the "Prediction and Evaluation" tab (list of 13 lists for a single frame).'. Saw this is one of the threads. Could you tell me what these 13 lists are? Frame with annotation expects [[row['x1'],row['y1']], [row['x2'],row['y2']], [row['x3'],row['y3']], [row['x4'],row['y4']]] these
Posted by: prak @ April 19, 2023, 4:07 p.m.Hi,
For more details and explanations, please refer to the first section: "Predictions" in "Prediction and Evaluation" tab.
Neta,
MAFAT Challenge Team