Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-04-11 12:41:07 +02:00
parent 835f975228
commit cbd5347cc3
3 changed files with 5 additions and 5 deletions
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1
models.py
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@ -178,6 +178,7 @@ class Darknet(nn.Module):
self.module_defs[0]['cfg'] = cfg_path self.module_defs[0]['cfg'] = cfg_path
self.module_defs[0]['height'] = img_size self.module_defs[0]['height'] = img_size
self.hyperparams, self.module_list = create_modules(self.module_defs) self.hyperparams, self.module_list = create_modules(self.module_defs)
self.yolo_layers = get_yolo_layers(self)
def forward(self, x, var=None): def forward(self, x, var=None):
img_size = x.shape[-1] img_size = x.shape[-1]

3
train.py
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@ -48,8 +48,7 @@ def train(
cutoff = -1 # backbone reaches to cutoff layer cutoff = -1 # backbone reaches to cutoff layer
start_epoch = 0 start_epoch = 0
best_loss = float('inf') best_loss = float('inf')
yl = get_yolo_layers(model) # yolo layers nf = int(model.module_defs[model.yolo_layers[0] - 1]['filters']) # yolo layer size (i.e. 255)
nf = int(model.module_defs[yl[0] - 1]['filters']) # yolo layer size (i.e. 255)
if resume: # Load previously saved model if resume: # Load previously saved model
if transfer: # Transfer learning if transfer: # Transfer learning

6
utils/utils.py
View File

@ -288,8 +288,8 @@ def build_targets(model, targets):
model = model.module model = model.module
txy, twh, tcls, indices = [], [], [], [] txy, twh, tcls, indices = [], [], [], []
for i, layer in enumerate(get_yolo_layers(model)): for i in model.yolo_layers:
layer = model.module_list[layer][0] layer = model.module_list[i][0]
# iou of targets-anchors # iou of targets-anchors
gwh = targets[:, 4:6] * layer.nG gwh = targets[:, 4:6] * layer.nG
@ -523,7 +523,7 @@ def plot_results(start=0, stop=0): # from utils.utils import *; plot_results()
x = range(start, min(stop, n) if stop else n) x = range(start, min(stop, n) if stop else n)
for i in range(10): for i in range(10):
plt.subplot(2, 5, i + 1) plt.subplot(2, 5, i + 1)
plt.plot(x, results[i, x].clip(max=500), marker='.', label=f) plt.plot(x, results[i, x].clip(max=500), marker='.', label=f.replace('.txt',''))
plt.title(s[i]) plt.title(s[i])
if i == 0: if i == 0:
plt.legend() plt.legend()