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[~] Refactor

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This commit is contained in:
Siarhei Siniak 2021-07-23 10:07:09 +03:00
parent 8c37e47869
commit bab23747e3
1 changed files with 84 additions and 79 deletions
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163
python/tasks/mlb_player.py
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@ -1019,88 +1019,93 @@ def kernel_15(
)
)
t2 = 'baseball glove'
t3 = o_14['o_13']['t1']
t4 = numpy.where(t3.name.data == t2)[0]
for t2 in [
'baseball glove',
'baseball bat',
'sports ball',
'person',
]:
t28 = t2.replace(' ', '-')
t3 = o_14['o_13']['t1']
t4 = numpy.where(t3.name.data == t2)[0]
numpy.random.seed(0)
t22 = numpy.random.choice(t4, 10)
pprint.pprint(t22)
import tqdm
t24 = []
t27 = []
for t5 in tqdm.tqdm(t22):
t6 = t3.video_path.data[t5]
t7 = t3.frame_id.data[t5]
t8 = t3.to_dataframe().iloc[t5]
#pprint.pprint([t6, t7])
#pprint.pprint(t8)
numpy.random.seed(0)
t22 = numpy.random.choice(t4, 10)
pprint.pprint(t22)
import tqdm
t24 = []
t27 = []
for t5 in tqdm.tqdm(t22):
t6 = t3.video_path.data[t5]
t7 = t3.frame_id.data[t5]
t8 = t3.to_dataframe().iloc[t5]
#pprint.pprint([t6, t7])
#pprint.pprint(t8)
import cv2
import matplotlib.pyplot
import cv2
import matplotlib.pyplot
t9 = cv2.VideoCapture(t6)
t9.set(cv2.CAP_PROP_POS_FRAMES, t7)
t10 = t9.read()
t9.release()
t11 = t10[1]
t12 = cv2.cvtColor(t11, cv2.COLOR_BGR2RGB)
t13 = t12.copy()
t15 = numpy.array([t8.xcenter, t8.ycenter, t8.width, t8.height])
t16 = numpy.array([t13.shape[1], t13.shape[0], t13.shape[1], t13.shape[0]])
t17 = t15 * t16
t18 = t17[:2] - t17[2:] / 2
t19 = t17[:2] + t17[2:] / 2
t20 = numpy.array([
t18[0], t18[1],
t19[0], t19[1],
])
t21 = numpy.round(t20).astype(numpy.int32)
t14 = cv2.rectangle(
t13,
tuple(t21[:2]),
tuple(t21[2:]),
(0, 255, 0),
1,
)
f = matplotlib.pyplot.figure()
matplotlib.pyplot.title(
'name %s, score %s, frame_id %d' % (
t8.name,
t8.confidence,
t8.frame_id,
t9 = cv2.VideoCapture(t6)
t9.set(cv2.CAP_PROP_POS_FRAMES, t7)
t10 = t9.read()
t9.release()
t11 = t10[1]
t12 = cv2.cvtColor(t11, cv2.COLOR_BGR2RGB)
t13 = t12.copy()
t15 = numpy.array([t8.xcenter, t8.ycenter, t8.width, t8.height])
t16 = numpy.array([t13.shape[1], t13.shape[0], t13.shape[1], t13.shape[0]])
t17 = t15 * t16
t18 = t17[:2] - t17[2:] / 2
t19 = t17[:2] + t17[2:] / 2
t20 = numpy.array([
t18[0], t18[1],
t19[0], t19[1],
])
t21 = numpy.round(t20).astype(numpy.int32)
t14 = cv2.rectangle(
t13,
tuple(t21[:2]),
tuple(t21[2:]),
(0, 255, 0),
1,
)
f = matplotlib.pyplot.figure()
matplotlib.pyplot.title(
'name %s, score %s, frame_id %d' % (
t8.name,
t8.confidence,
t8.frame_id,
)
)
matplotlib.pyplot.imshow(t14)
t25 = 'kernel_15-%s-%05d.jpg' % (
t28,
t7,
)
f.savefig(t25)
t24.append(t25)
matplotlib.pyplot.close(f)
t27.append([t8, t21])
pprint.pprint(
pandas.concat([
o[0]
for o in t27
], axis=1).T
)
matplotlib.pyplot.imshow(t14)
t28 = t8['name'].replace(' ', '-')
t25 = 'kernel_15-%s-%05d.jpg' % (
t28,
t7,
t23 = 'output-%s.gif' % t28
if os.path.exists(t23):
subprocess.check_call(['rm', t23])
subprocess.check_call(
[
'convert',
'-delay',
'100',
'-loop',
'0',
*t24,
t23,
]
)
f.savefig(t25)
t24.append(t25)
matplotlib.pyplot.close(f)
t27.append([t8, t21])
pprint.pprint(
pandas.concat([
o[0]
for o in t27
], axis=1).T
)
t23 = 'output.gif'
if os.path.exists(t23):
subprocess.check_call(['rm', t23])
subprocess.check_call(
[
'convert',
'-delay',
'100',
'-loop',
'0',
*t24,
t23,
]
)