AP for aeroplane = -1.0000
AP for bicycle = -1.0000
AP for bird = -1.0000
AP for boat = -1.0000
AP for bottle = -1.0000
AP for bus = -1.0000
AP for car = -1.0000
AP for cat = -1.0000
AP for chair = -1.0000
AP for cow = -1.0000
AP for diningtable = -1.0000
AP for dog = -1.0000
AP for horse = -1.0000
AP for motorbike = -1.0000
AP for person = 0.0183
AP for pottedplant = -1.0000
AP for sheep = -1.0000
AP for sofa = -1.0000
AP for train = -1.0000
AP for tvmonitor = -1.0000
Mean AP = -0.9491
I have edited the test.py to skip model exist checking
(since tf r1.1 saving as .index .meta .data three file instead one)
But I didn't think that is the reason fail training.
Hi, I have training VGG - faster-rcnn example follows the Readme.md
with
and tested with
AP for aeroplane = -1.0000 AP for bicycle = -1.0000 AP for bird = -1.0000 AP for boat = -1.0000 AP for bottle = -1.0000 AP for bus = -1.0000 AP for car = -1.0000 AP for cat = -1.0000 AP for chair = -1.0000 AP for cow = -1.0000 AP for diningtable = -1.0000 AP for dog = -1.0000 AP for horse = -1.0000 AP for motorbike = -1.0000 AP for person = 0.0183 AP for pottedplant = -1.0000 AP for sheep = -1.0000 AP for sofa = -1.0000 AP for train = -1.0000 AP for tvmonitor = -1.0000 Mean AP = -0.9491
I have edited the test.py to skip model exist checking (since tf r1.1 saving as .index .meta .data three file instead one) But I didn't think that is the reason fail training.
Are there anyone with this similar problem??
my tensorflow version r1.1