validation_results_paddlepaddle.md

Validation results for the models inferring using PaddlePaddle

Image classification

Test image #1

Data source: ImageNet

Image resolution: 709 x 510

Model	Parameters	Python API
resnet-50	Mean values - [123.675,116.28,103.53], scale value - [58.395,57.12,57.375]	0.9931559 Granny Smith 0.0009120 piggy bank, penny bank 0.0007721 bell pepper 0.0007689 tennis ball 0.0005548 candle, taper, wax light
PPLCNet_x1_0_infer	Mean values - [123.675,116.28,103.53], scale value - [58.395,57.12,57.375]	0.2785943 Granny Smith 0.2241544 piggy bank, penny bank 0.0404602 saltshaker, salt shaker 0.0131707 soap dispenser 0.0114298 lemon

Test image #2

Data source: ImageNet

Image resolution: 500 x 500

Model	Parameters	Python API
resnet-50	Mean values - [123.675,116.28,103.53], scale value - [58.395,57.12,57.375]	0.9891654 junco, snowbird 0.0044086 chickadee 0.0033522 water ouzel, dipper 0.0014910 brambling, Fringilla montifringilla 0.0003624 indigo bunting, indigo finch, indigo bird, Passerina cyanea
PPLCNet_x1_0_infer	Mean values - [123.675,116.28,103.53], scale value - [58.395,57.12,57.375]	0.8259031 junco, snowbird 0.0340593 brambling, Fringilla montifringilla 0.0055266 chickadee 0.0050722 house finch, linnet, Carpodacus mexicanus 0.0034595 bulbul

Test image #3

Data source: ImageNet

Image resolution: 333 x 500

Model	Parameters	Python API
resnet-50	Mean values - [123.675,116.28,103.53], scale value - [58.395,57.12,57.375]	0.3656897 liner, ocean liner 0.1008371 container ship, containership, container vessel 0.0759774 dock, dockage, docking facility 0.0707850 lifeboat 0.0556011 breakwater, groin, groyne, mole, bulwark, seawall, jetty
PPLCNet_x1_0_infer	Mean values - [123.675,116.28,103.53], scale value - [58.395,57.12,57.375]	0.1249109 submarine, pigboat, sub, U-boat 0.1198353 breakwater, groin, groyne, mole, bulwark, seawall, jetty 0.0568103 liner, ocean liner 0.0351734 lifeboat 0.0326451 dock, dockage, docking facility