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Fix get_v3_boxes and Clean up YOLO utils
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@taehoonlee
taehoonlee committed May 7, 2018
1 parent 45f067f commit 93bd531
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Showing 5 changed files with 33 additions and 33 deletions.
2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -308,7 +308,7 @@ with tf.Session() as sess:

| | mAP | Size | Speed | FPS | References |
|------------------------------------------------------------------------|--------|--------|-------|-------|------------|
| [YOLOv3VOC](tensornets/references/yolos.py#L175) | 0.7247 | 62M | 24.09 | 41.51 | [[paper]](https://pjreddie.com/media/files/papers/YOLOv3.pdf) [[darknet]](https://pjreddie.com/darknet/yolo/) [[darkflow]](https://github.com/thtrieu/darkflow) |
| [YOLOv3VOC](tensornets/references/yolos.py#L175) | 0.7423 | 62M | 24.09 | 41.51 | [[paper]](https://pjreddie.com/media/files/papers/YOLOv3.pdf) [[darknet]](https://pjreddie.com/darknet/yolo/) [[darkflow]](https://github.com/thtrieu/darkflow) |
| [YOLOv2VOC](tensornets/references/yolos.py#L195) | 0.7320 | 51M | 14.75 | 67.80 | [[paper]](https://arxiv.org/abs/1612.08242) [[darknet]](https://pjreddie.com/darknet/yolov2/) [[darkflow]](https://github.com/thtrieu/darkflow) |
| [TinyYOLOv2VOC](tensornets/references/yolos.py#L205) | 0.5303 | 16M | 6.534 | 153.0 | [[paper]](https://arxiv.org/abs/1612.08242) [[darknet]](https://pjreddie.com/darknet/yolov2/) [[darkflow]](https://github.com/thtrieu/darkflow) |
| [FasterRCNN\_ZF\_VOC](tensornets/references/rcnns.py#L151) | 0.4466 | 59M | 241.4 | 3.325 | [[paper]](https://arxiv.org/abs/1506.01497) [[caffe]](https://github.com/rbgirshick/py-faster-rcnn) [[roi-pooling]](https://github.com/deepsense-ai/roi-pooling) |
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30 changes: 22 additions & 8 deletions tensornets/references/darkflow_utils/get_boxes.pyx
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Expand Up @@ -5,8 +5,9 @@ cimport numpy as np
cimport cython
ctypedef np.float_t DTYPE_t
from libc.math cimport exp
from libc.math cimport pow
from .box import BoundBox
from .nms cimport NMS
from .nms import NMS

#expit
@cython.boundscheck(False) # turn off bounds-checking for entire function
Expand Down Expand Up @@ -52,7 +53,7 @@ cdef void _softmax_c(float* x, int classes):
@cython.cdivision(True)
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
def yolov3_box(meta,np.ndarray[float,ndim=3] net_out_in):
def _yolov3_box(meta,np.ndarray[float,ndim=3] net_out_in,scale_idx):
cdef:
np.intp_t H, W, _, C, B, row, col, box_loop, class_loop
np.intp_t row1, col1, box_loop1,index,index2
Expand All @@ -61,10 +62,12 @@ def yolov3_box(meta,np.ndarray[float,ndim=3] net_out_in):
double[:] anchors = np.asarray(meta['anchors'])
list boxes = list()

H, W, _ = meta['out_size']
H, W = net_out_in.shape[:2]
C = meta['classes']
B = 3 # meta['num']
anchor_idx = meta['anchor_idx']
anchor_idx = 6 - 3 * scale_idx
Hin = H * pow(2, 5 - scale_idx)
Win = W * pow(2, 5 - scale_idx)

cdef:
float[:, :, :, ::1] net_out = net_out_in.reshape([H, W, B, net_out_in.shape[2]/B])
Expand All @@ -80,8 +83,8 @@ def yolov3_box(meta,np.ndarray[float,ndim=3] net_out_in):
Bbox_pred[row, col, box_loop, 4] = expit_c(Bbox_pred[row, col, box_loop, 4])
Bbox_pred[row, col, box_loop, 0] = (col + expit_c(Bbox_pred[row, col, box_loop, 0])) / W
Bbox_pred[row, col, box_loop, 1] = (row + expit_c(Bbox_pred[row, col, box_loop, 1])) / H
Bbox_pred[row, col, box_loop, 2] = exp(Bbox_pred[row, col, box_loop, 2]) * anchors[2 * (box_loop + anchor_idx) + 0] / (W * 32)
Bbox_pred[row, col, box_loop, 3] = exp(Bbox_pred[row, col, box_loop, 3]) * anchors[2 * (box_loop + anchor_idx) + 1] / (H * 32)
Bbox_pred[row, col, box_loop, 2] = exp(Bbox_pred[row, col, box_loop, 2]) * anchors[2 * (box_loop + anchor_idx) + 0] / Win
Bbox_pred[row, col, box_loop, 3] = exp(Bbox_pred[row, col, box_loop, 3]) * anchors[2 * (box_loop + anchor_idx) + 1] / Hin
#SOFTMAX BLOCK, no more pointer juggling
for class_loop in range(C):
arr_max=max_c(arr_max,Classes[row,col,box_loop,class_loop])
Expand All @@ -97,7 +100,18 @@ def yolov3_box(meta,np.ndarray[float,ndim=3] net_out_in):


#NMS
return NMS(np.ascontiguousarray(probs).reshape(H*W*B,C), np.ascontiguousarray(Bbox_pred).reshape(H*B*W,5))
return np.ascontiguousarray(probs).reshape(H*W*B,C), np.ascontiguousarray(Bbox_pred).reshape(H*B*W,5)


#BOX CONSTRUCTOR
@cython.cdivision(True)
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
def yolov3_box(meta,np.ndarray[float,ndim=3] out0,np.ndarray[float,ndim=3] out1,np.ndarray[float,ndim=3] out2):
a0, b0 = _yolov3_box(meta, out0, 0)
a1, b1 = _yolov3_box(meta, out1, 1)
a2, b2 = _yolov3_box(meta, out2, 2)
return NMS(np.concatenate([a2, a1, a0], axis=0), np.concatenate([b2, b1, b0], axis=0))


#BOX CONSTRUCTOR
Expand All @@ -113,7 +127,7 @@ def yolov2_box(meta,np.ndarray[float,ndim=3] net_out_in):
double[:] anchors = np.asarray(meta['anchors'])
list boxes = list()

H, W, _ = meta['out_size']
H, W = net_out_in.shape[:2]
C = meta['classes']
B = meta['num']

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11 changes: 0 additions & 11 deletions tensornets/references/darkflow_utils/nms.pxd
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2 changes: 1 addition & 1 deletion tensornets/references/darkflow_utils/nms.pyx
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Expand Up @@ -62,7 +62,7 @@ cdef float box_iou_c(float ax, float ay, float aw, float ah, float bx, float by,
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
@cython.cdivision(True)
cdef NMS(float[:, ::1] final_probs , float[:, ::1] final_bbox):
def NMS(np.ndarray[float,ndim=2] final_probs, np.ndarray[float,ndim=2] final_bbox):
cdef list boxes = list()
cdef set indices = set()
cdef:
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21 changes: 9 additions & 12 deletions tensornets/references/yolo_utils.py
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Expand Up @@ -75,15 +75,14 @@ def get_v3_boxes(opts, outs, source_size, threshold=0.1):
h, w = source_size
boxes = [[] for _ in xrange(opts['classes'])]
opts['thresh'] = threshold
for i in range(3):
opts['out_size'] = list(outs[i][0].shape)
opts['anchor_idx'] = 6 - 3 * i
o = np.array(outs[i][0], dtype=np.float32)
results = yolov3_box(opts, o)
for b in results:
idx, box = parse_box(b, threshold, w, h)
if idx is not None:
boxes[idx].append(box)
results = yolov3_box(opts,
np.array(outs[0][0], dtype=np.float32),
np.array(outs[1][0], dtype=np.float32),
np.array(outs[2][0], dtype=np.float32))
for b in results:
idx, box = parse_box(b, threshold, w, h)
if idx is not None:
boxes[idx].append(box)
for i in xrange(opts['classes']):
boxes[i] = np.asarray(boxes[i], dtype=np.float32)
return boxes
Expand All @@ -93,9 +92,7 @@ def get_v2_boxes(opts, outs, source_size, threshold=0.1):
h, w = source_size
boxes = [[] for _ in xrange(opts['classes'])]
opts['thresh'] = threshold
opts['out_size'] = list(outs[0].shape)
o = np.array(outs[0], dtype=np.float32)
results = yolov2_box(opts, o)
results = yolov2_box(opts, np.array(outs[0], dtype=np.float32))
for b in results:
idx, box = parse_box(b, threshold, w, h)
if idx is not None:
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