From f4dc0d84e4c320480273ddeb6ad768db47b0a254 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Thu, 18 Apr 2019 12:27:28 +0200 Subject: [PATCH] updates --- train.py | 37 +++++++++++++++++++------------------ 1 file changed, 19 insertions(+), 18 deletions(-) diff --git a/train.py b/train.py index 25f88de6..82cd3642 100644 --- a/train.py +++ b/train.py @@ -11,14 +11,14 @@ from utils.datasets import * from utils.utils import * # Initialize hyperparameters -hyp = {'k': 8.4875, # loss multiple - 'xy': 0.079756, # xy loss fraction - 'wh': 0.010461, # wh loss fraction - 'cls': 0.02105, # cls loss fraction - 'conf': 0.88873, # conf loss fraction - 'iou_t': 0.1, # iou target-anchor training threshold - 'lr0': 0.001, # initial learning rate - 'lrf': -2., # final learning rate = lr0 * (10 ** lrf) +hyp = {'k': 6.927, # loss multiple + 'xy': 0.07556, # xy loss fraction + 'wh': 0.008074, # wh loss fraction + 'cls': 0.01113, # cls loss fraction + 'conf': 0.9052, # conf loss fraction + 'iou_t': 0.06154, # iou target-anchor training threshold + 'lr0': 0.001136, # initial learning rate + 'lrf': -2.52, # final learning rate = lr0 * (10 ** lrf) 'momentum': 0.9, # SGD momentum 'weight_decay': 0.0005, # optimizer weight decay } @@ -89,7 +89,7 @@ def train( # Scheduler (reduce lr at epochs 218, 245, i.e. batches 400k, 450k) # lf = lambda x: 1 - x / epochs # linear ramp to zero # lf = lambda x: 10 ** (-2 * x / epochs) # exp ramp to lr0 * 1e-2 - lf = lambda x: 1 - 10 ** (-2 * (1 - x / epochs)) # inv exp ramp to lr0 * 1e-2 + lf = lambda x: 1 - 10 ** (hyp['lrf'] * (1 - x / epochs)) # inv exp ramp to lr0 * 1e-2 scheduler = optim.lr_scheduler.LambdaLR(optimizer, lr_lambda=lf, last_epoch=start_epoch - 1) # scheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=[218, 245], gamma=0.1, last_epoch=start_epoch - 1) @@ -347,12 +347,13 @@ if __name__ == '__main__': else: hyp = old_hyp.copy() # reset hyp to - -import numpy as np -import matplotlib.pyplot as plt -a = np.loadtxt('evolve.txt') -x = a[:,3] -fig = plt.figure(figsize=(14, 7)) -for i in range(1,10): - plt.subplot(2,5,i) - plt.plot(x,a[:,i+5],'.') + # # Plot results + # import numpy as np + # import matplotlib.pyplot as plt + # + # a = np.loadtxt('evolve.txt') + # x = a[:, 3] + # fig = plt.figure(figsize=(14, 7)) + # for i in range(1, 10): + # plt.subplot(2, 5, i) + # plt.plot(x, a[:, i + 5], '.')