seewalker

# Assume Xgt is pixelwise, 1-of-k vector encoded ground truth.
# So, Xgt has dimensions (img_height,img_width,num_classes+1), such that the location of the '1' value in the third dimension indicates the true class.
# and that location being at "num_classes" indicates lack of available ground truth (i.e. a background pixel).
gtexists = tf.less(tf.argmax(Xgt,2),num_classes)
fg_gt = tf.boolean_mask(Xgt,gtexists)
bg_gt = tf.boolean_mask(Xgt,tf.logical_not(gtexists))
# fg_gt is of shape (?,num_classes+1) because the actual configuration of foreground/background pixels depends on the particular
# batch of input, so it is not known when constructing the computational graph here.

# Now, we can define separate error terms for errors where a foreground pixel is misclassified

seewalker

func phasset2json(asset:PHAsset) -> String {
    let (username,password) = ("","")
    let authData = "\(username):\(password)".dataUsingEncoding(NSUTF8StringEncoding)!
    let encoded = authData.base64EncodedStringWithOptions(.Encoding76CharacterLineLength)
    let basicAuthHeader = "Basic \(encoded)"
    let urlPath: String = "https://server.com/blah?param=2"
    let url: NSURL = NSURL(string: urlPath)!
    var request: NSMutableURLRequest = NSMutableURLRequest(URL: url)
    let boundary = NSString(format: "---------------------------14737809831466499882746641449")
    request.HTTPMethod = "POST"

seewalker

include ../config.h

.c.o:
    $(CC) -c -Dflex $(COPTFLAGS) $(CFLAGS) $(AMBERCFLAGS) $(RISMSFF) $(NETCDFINC) -o $@ $<

OBJS = binpos.o conjgrad.o lmodC.o memutil.o nblist.o newton.o nmode.o \
    prm.o rand2.o sasad.o sff.o time.o xminC.o AmberNetcdf.o atomic_number.o $(SFF_RISM_INTERFACE)


install: libsff hcp_getpdb