Reading annotation for 4951/4952
Reading annotation for 4952/4952
Saving cached annotations to /home/sagarwal/tf-faster-rcnn/data/VOCdevkit2007/annotations_cache/test_annots.pkl
AP for aeroplane = 0.0000
AP for bicycle = 0.0000
AP for bird = 0.0000
AP for boat = 0.0000
AP for bottle = 0.0000
AP for bus = 0.0000
AP for car = 0.0000
AP for cat = 0.0000
AP for chair = 0.0000
AP for cow = 0.0000
AP for diningtable = 0.0000
AP for dog = 0.0000
AP for horse = 0.0000
AP for motorbike = 0.0000
AP for person = 0.0000
AP for pottedplant = 0.0000
AP for sheep = 0.0000
AP for sofa = 0.0000
AP for train = 0.0000
AP for tvmonitor = 0.0000
Mean AP = 0.0000
Results computed with the unofficial Python eval code.
Results should be very close to the official MATLAB eval code.
Recompute with ./tools/reval.py --matlab ... for your paper.
-- Thanks, The Management
I get zeros everywhere. Any idea?
Reading annotation for 4951/4952 Reading annotation for 4952/4952 Saving cached annotations to /home/sagarwal/tf-faster-rcnn/data/VOCdevkit2007/annotations_cache/test_annots.pkl AP for aeroplane = 0.0000 AP for bicycle = 0.0000 AP for bird = 0.0000 AP for boat = 0.0000 AP for bottle = 0.0000 AP for bus = 0.0000 AP for car = 0.0000 AP for cat = 0.0000 AP for chair = 0.0000 AP for cow = 0.0000 AP for diningtable = 0.0000 AP for dog = 0.0000 AP for horse = 0.0000 AP for motorbike = 0.0000 AP for person = 0.0000 AP for pottedplant = 0.0000 AP for sheep = 0.0000 AP for sofa = 0.0000 AP for train = 0.0000 AP for tvmonitor = 0.0000 Mean AP = 0.0000
Results computed with the unofficial Python eval code. Results should be very close to the official MATLAB eval code. Recompute with
./tools/reval.py --matlab ...
for your paper. -- Thanks, The Management