def run(self, para=None):
url = para['repo']
if 'github.com' in url:
if url[-4:] == '.git':
url = url.replace('.git', '/archive/master.zip')
elif url[-4:] != '.zip':
url = url + '/archive/master.zip'
domain, name = url.split('/')[-4:-2]
else:
domain, name = (url[:-4].replace('.', '-')).split('/')[-2:]
domain, name = domain.replace('_', '-'), name.replace('_', '-')
IPy.set_info('downloading plugin from %s' % para['repo'])
urlretrieve(url,
os.path.join(path_cache, domain + '_' + name + '.zip'),
lambda a, b, c, p=self: Schedule(a, b, c, p))
zipf = zipfile.ZipFile(
os.path.join(path_cache, domain + '_' + name + '.zip'))
folder = zipf.namelist()[0]
zipf.extractall(path_cache)
destpath = os.path.join(path_plgs,
domain + '_' + folder.replace('-master', ''))
if os.path.exists(destpath): shutil.rmtree(destpath)
os.rename(os.path.join(path_cache, folder), destpath)
zipf.close()
IPy.set_info('installing requirement liberies')
self.prgs = (None, 1)
cmds = [
sys.executable, '-m', 'pip', 'install', '-r',
'%s/requirements.txt' % destpath
]
subprocess.call(cmds)
IPy.reload_plgs(True, True, True, True)
def info(self, ips, cur):
k, u = ips.unit
l, r, t, b = self.lt, self.rt, self.tp, self.bm
IPy.set_info('Rectangle : x:%.1f y:%.1f w:%.1f h:%.1f S:%.1f' %
(min(l, r) * k, min(t, b) * k, abs(r - l) * k,
abs(b - t) * k, abs(
(r - l) * (b - t) / 4 * np.pi * k**2)))
def mouse_move(self, ips, x, y, btn, **key):
if 'trans' in ips.data:
trans = np.array(ips.data['trans']).reshape((2, 3))
jw = np.dot(trans[:, 1:], (x, y)) + trans[:, 0]
IPy.set_info('X:%d Y:%d ==> N:%.4f, E:%.4f' % (x, y, jw[0], jw[1]))
if not 'adjc' in ips.data: return
lim = 5.0 / key['canvas'].scale
if btn == None:
self.cursor = wx.CURSOR_CROSS
ison = self.pick(x, y, ips.data['adjc'], lim)
if ison != None:
self.cursor = wx.CURSOR_HAND
elif btn == 1:
self.curobj[0], self.curobj[1] = x, y
self.update(ips)
def runasyn(self, wb, info, key, para=None, callback=None):
TaskManager.add(self)
for i in para:
if i in key and key[i][0] == 'img':
ips = ImageManager.get(para[i])
para[i] = ips if ips is None else ips.img
if i in key and key[i][0] == 'tab':
tps = TableManager.get(para[i])
para[i] = tps if tps is None else tps.data
start = time()
xlreport.fill_value(wb, info, para)
wb.save(para['path'])
IPy.set_info('%s: cost %.3fs' % (self.title, time() - start))
TaskManager.remove(self)
if callback != None: callback()
def mouse_down(self, ips, x, y, btn, **key):
if btn != 1: return
msk = flood(ips.img, (int(y), int(x)), connectivity=0, tolerance=0)
conts = find_contours(msk, 0.5, 'high')
conts = conts[0][:, ::-1]
ips.mark = Mark(conts)
trans = ips.img.mat
jw = np.dot(trans[:, 1:], conts.T).T + trans[:, 0]
osrprj = osr.SpatialReference()
osrprj.ImportFromWkt(ips.img.crs)
osrgeo = osr.SpatialReference()
osrgeo.ImportFromEPSG(3857)
ct = osr.CoordinateTransformation(osrprj, osrgeo)
xy = ct.TransformPoints(jw)
polygon = Polygon(xy)
c = polygon.centroid
IPy.set_info('At N:%.4f, E:%.4f Area:%.4f' % (c.x, c.y, polygon.area))
ips.update()
def run(self, ips, imgs, para = None):
k = para['diag']/np.sqrt((np.array(ips.img.shape)**2).sum())
size = tuple((np.array(ips.img.shape)*k).astype(np.int16))
IPy.set_info('down sample...')
news = []
for img in imgs:
if k!=0: img = tf.resize(img, size)
if para['sigma']!=0:
img = ndimg.gaussian_filter(img, para['sigma'])
news.append(img)
IPy.set_info('register...')
sr = StackReg(eval('StackReg.%s'%para['trans']))
sr.register_stack(np.array(news), reference=para['ref'])
mats = sr._tmats.reshape((sr._tmats.shape[0],-1))
if k!=0: mats[:,[0,1,3,4,6,7]] *= k
if k!=0: mats[:,[0,1,2,3,4,5]] /= k
if para['tab']: IPy.show_table(pd.DataFrame(
mats, columns=['A%d'%(i+1) for i in range(mats.shape[1])]), title='%s-Tmats'%ips.title)
if para['new'] == 'None': return
IPy.set_info('transform...')
for i in range(sr._tmats.shape[0]):
tform = tf.ProjectiveTransform(matrix=sr._tmats[i])
img = tf.warp(imgs[i], tform)
img -= imgs[i].min(); img *= imgs[i].max() - imgs[i].min()
if para['new'] == 'Inplace': imgs[i][:] = img
if para['new'] == 'New': news[i] = img.astype(ips.img.dtype)
self.progress(i, len(imgs))
if para['new'] == 'New': IPy.show_img(news, '%s-reg'%ips.title)
def run(self, ips, imgs, para=None):
lim = np.zeros([len(imgs), 2], dtype=imgs[0].dtype)
dic = {np.uint8: 255, np.uint16: 65535, np.float32: 1, np.float64: 1}
IPy.set_info('count range ...')
for i in range(len(imgs)):
lim[i] = imgs[i].min(), imgs[i].max()
self.progress(i, len(imgs))
maxvalue = dic[imgs[0].dtype.type]
if not para['sb']: lim[:, 0] = 0
rg = lim[:, 0].min(), lim[:, 1].max()
if para['is3d']: lim[:] = rg
IPy.set_info('adjust range ...')
for i in range(len(imgs)):
if para['sb']: imgs[i] -= lim[i, 0]
np.multiply(imgs[i],
maxvalue / (lim[i].ptp()),
out=imgs[i],
casting='unsafe')
self.progress(i, len(imgs))
ips.range = 0, maxvalue
def on_mouseevent(self, me):
tool = self.ips.tool
if tool == None : tool = ToolsManager.curtool
x,y = self.to_data_coor(me.GetX(), me.GetY())
if me.Moving() and not me.LeftIsDown() and not me.RightIsDown() and not me.MiddleIsDown():
xx,yy = int(round(x)), int(round(y))
k, unit = self.ips.unit
if xx>=0 and xx<self.ips.img.shape[1] and yy>=0 and yy<self.ips.img.shape[0]:
IPy.set_info('Location:%.1f %.1f Value:%s'%(x*k, y*k, self.ips.img[yy,xx]))
if tool==None:return
sta = [me.AltDown(), me.ControlDown(), me.ShiftDown()]
if me.ButtonDown():tool.mouse_down(self.ips, x, y, me.GetButton(), alt=sta[0], ctrl=sta[1], shift=sta[2], canvas=self)
if me.ButtonUp():tool.mouse_up(self.ips, x, y, me.GetButton(), alt=sta[0], ctrl=sta[1], shift=sta[2], canvas=self)
if me.Moving():tool.mouse_move(self.ips, x, y, None, alt=sta[0], ctrl=sta[1], shift=sta[2], canvas=self)
btn = [me.LeftIsDown(), me.MiddleIsDown(), me.RightIsDown(),True].index(True)
if me.Dragging():tool.mouse_move(self.ips, x, y, 0 if btn==3 else btn+1, alt=sta[0], ctrl=sta[1], shift=sta[2], canvas=self)
wheel = np.sign(me.GetWheelRotation())
if wheel!=0:tool.mouse_wheel(self.ips, x, y, wheel, alt=sta[0], ctrl=sta[1], shift=sta[2], canvas=self)
if hasattr(tool, 'cursor'):
self.SetCursor(wx.Cursor(tool.cursor))
else : self.SetCursor(wx.Cursor(wx.CURSOR_ARROW))
def run(self, ips, imgs, para=None, preview=False):
if len(ips.imgs) == 1: ips.img[:] = ips.snap
key = {'chans': None, 'grade': para['grade'], 'w': para['w']}
key['items'] = [i for i in ['ori', 'blr', 'sob', 'eig'] if para[i]]
slir, slic = ips.get_rect()
labs = [i[slir, slic] for i in imgs]
ori = ImageManager.get(para['img']).imgs
if len(imgs) == 1: ori = [ImageManager.get(para['img']).img]
oris = [i[slir, slic] for i in ori]
IPy.set_info('extract features...')
feat, lab, key = feature.get_feature(oris,
labs,
key,
callback=self.progress)
IPy.set_info('training data...')
self.progress(None, 1)
model = self.classify(para)
model.fit(feat, lab)
IPy.set_info('predict data...')
if preview:
return feature.get_predict(oris,
model,
key,
labs,
callback=self.progress)
if len(imgs) == 1: ips.swap()
outs = feature.get_predict(oris, model, key, callback=self.progress)
nips = ImagePlus(outs, ips.title + 'rst')
nips.range, nips.lut = ips.range, ips.lut
nips.back, nips.chan_mode = ips.back, 0.4
IPy.show_ips(nips)
global model_para
model_para = model, key
def info(self, ips, cur):
if cur == None: return
IPy.set_info('Polygon: %.0f fragments' % len(self.body))
def info(self, ips, cur):
k, u = ips.unit
if cur==None:return
x, y = self.body[cur]
IPy.set_info('points:%.0f x:%.1f y:%.1f'%(len(self.body), x*k, y*k))
def mouse_move(self, ips, x, y, btn, **key):
if not isinstance(ips.img, GeoArray):
return IPy.set_info('No Coordinate')
trans = ips.img.mat
jw = np.dot(ips.img.mat[:, 1:], (x, y)) + ips.img.mat[:, 0]
IPy.set_info('X:%d Y:%d ==> N:%.4f, E:%.4f' % (x, y, jw[0], jw[1]))
def run(self, para=None):
IPy.set_info('update now, waiting...')
repo = self.repo('../')
client, remote_path = self.trans('https://github.com/Image-Py/imagepy.git')
a = client.fetch(remote_path, repo)
IPy.alert('imagepy update done!')
def info(self, ips, cur):
k, u = ips.unit
if cur == None: return
x, y = cur[0][cur[1]]
IPy.set_info('Line : points:%.0f x:%.1f y:%.1f' %
(len(cur[0]), x * k, y * k))
def run(self, para=None):
IPy.set_info('update now, waiting...')
self.download_zip()
self.deal_file()
#self.delete_cache()
IPy.alert('imagepy update done!')
