Merge pull request #534 from danielgordon10/yolov3

PYTHON3 IS GARBAGE GO AWAY DANIEL
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Joseph Redmon 2018-03-24 18:57:43 -07:00 committed by GitHub
commit 13413e9c0a
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4 changed files with 69 additions and 18 deletions

2
.gitignore vendored
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@ -25,3 +25,5 @@ ehthumbs.db
Icon?
Thumbs.db
*.swp
*.a
*.so

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@ -39,18 +39,17 @@ import darknet as dn
net = dn.load_net("cfg/tiny-yolo.cfg", "tiny-yolo.weights", 0)
meta = dn.load_meta("cfg/coco.data")
r = dn.detect(net, meta, "data/dog.jpg")
print r
print(r)
# scipy
arr= imread('data/dog.jpg')
im = array_to_image(arr)
r = detect2(net, meta, im)
print r
print(r)
# OpenCV
arr = cv2.imread('data/dog.jpg')
im = array_to_image(arr)
dn.rgbgr_image(im)
r = detect2(net, meta, im)
print r
print(r)

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@ -13,15 +13,14 @@ dn.set_gpu(0)
net = dn.load_net("cfg/yolo-thor.cfg", "/home/pjreddie/backup/yolo-thor_final.weights", 0)
meta = dn.load_meta("cfg/thor.data")
r = dn.detect(net, meta, "data/bedroom.jpg")
print r
print(r)
# And then down here you could detect a lot more images like:
r = dn.detect(net, meta, "data/eagle.jpg")
print r
print(r)
r = dn.detect(net, meta, "data/giraffe.jpg")
print r
print(r)
r = dn.detect(net, meta, "data/horses.jpg")
print r
print(r)
r = dn.detect(net, meta, "data/person.jpg")
print r
print(r)

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@ -13,9 +13,21 @@ def sample(probs):
return len(probs)-1
def c_array(ctype, values):
arr = (ctype*len(values))()
arr[:] = values
return arr
new_values = values.ctypes.data_as(POINTER(ctype))
return new_values
def array_to_image(arr):
import numpy as np
# need to return old values to avoid python freeing memory
arr = arr.transpose(2,0,1)
c = arr.shape[0]
h = arr.shape[1]
w = arr.shape[2]
arr = np.ascontiguousarray(arr.flat, dtype=np.float32) / 255.0
data = arr.ctypes.data_as(POINTER(c_float))
im = IMAGE(w,h,c,data)
return im, arr
class BOX(Structure):
_fields_ = [("x", c_float),
@ -43,7 +55,6 @@ class METADATA(Structure):
("names", POINTER(c_char_p))]
#lib = CDLL("/home/pjreddie/documents/darknet/libdarknet.so", RTLD_GLOBAL)
lib = CDLL("libdarknet.so", RTLD_GLOBAL)
lib.network_width.argtypes = [c_void_p]
@ -142,6 +153,26 @@ def detect(net, meta, image, thresh=.5, hier_thresh=.5, nms=.45):
free_detections(dets, num)
return res
def detect_numpy(net, meta, image, thresh=.5, hier_thresh=.5, nms=.45):
im, arr = array_to_image(image)
num = c_int(0)
pnum = pointer(num)
predict_image(net, im)
dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, None, 0, pnum)
num = pnum[0]
if (nms): do_nms_obj(dets, num, meta.classes, nms);
res = []
for j in range(num):
for i in range(meta.classes):
if dets[j].prob[i] > 0:
b = dets[j].bbox
res.append((meta.names[i], dets[j].prob[i], (b.x, b.y, b.w, b.h)))
res = sorted(res, key=lambda x: -x[1])
free_detections(dets, num)
return res
if __name__ == "__main__":
#net = load_net("cfg/densenet201.cfg", "/home/pjreddie/trained/densenet201.weights", 0)
#im = load_image("data/wolf.jpg", 0, 0)
@ -150,7 +181,27 @@ if __name__ == "__main__":
#print r[:10]
net = load_net("cfg/tiny-yolo.cfg", "tiny-yolo.weights", 0)
meta = load_meta("cfg/coco.data")
r = detect(net, meta, "data/dog.jpg")
print r
import scipy.misc
import time
'''
t_start = time.time()
for ii in range(100):
r = detect(net, meta, 'data/dog.jpg')
print(time.time() - t_start)
print(r)
image = scipy.misc.imread('data/dog.jpg')
for ii in range(100):
scipy.misc.imsave('/tmp/image.jpg', image)
r = detect(net, meta, '/tmp/image.jpg')
print(time.time() - t_start)
print(r)
'''
image = scipy.misc.imread('data/dog.jpg')
t_start = time.time()
for ii in range(100):
r = detect_numpy(net, meta, image)
print(time.time() - t_start)
print(r)