Minor fixes

AlexeyAB

2018-05-23 eef9f8e5bb9fdbe22c6301a56f12e315f9ac64d9

 darknet.py

@@ -78,13 +78,14 @@
#lib = CDLL("darknet.so", RTLD_GLOBAL)
hasGPU = True
if os.name == "nt":
    winGPUdll = "yolo_cpp_dll.dll"
    winNoGPUdll = "yolo_cpp_dll_nogpu.dll"
    cwd = os.path.dirname(__file__)
    os.environ['PATH'] = cwd + ';' + os.environ['PATH']
    winGPUdll = os.path.join(cwd, "yolo_cpp_dll.dll")
    winNoGPUdll = os.path.join(cwd, "yolo_cpp_dll_nogpu.dll")
    envKeys = list()
    for k, v in os.environ.items():
        envKeys.append(k)
    try:
        tmp = os.environ["CUDA_HOME"]
        try:
            tmp = os.environ["FORCE_CPU"].lower()
            if tmp in ["1", "true", "yes", "on"]:
@@ -97,28 +98,28 @@
                if int(os.environ['CUDA_VISIBLE_DEVICES']) < 0:
                    raise ValueError("ForceCPU")
            try:
                # Check a global
                global DARKNET_FORCE_CPU
                if DARKNET_FORCE_CPU:
                    raise ValueError("ForceCPU")
            except NameError:
                pass
            # print(os.environ.keys())
            print("FORCE_CPU flag undefined, proceeding with GPU")
            # print("FORCE_CPU flag undefined, proceeding with GPU")
        if not os.path.exists(winGPUdll):
            raise ValueError("NoDLL")
        lib = CDLL(winGPUdll, RTLD_GLOBAL)
    except (KeyError, ValueError):
        print("Notice: GPU-free mode")
        hasGPU = False
        if os.path.exists(winNoGPUdll):
            lib = CDLL(winNoGPUdll, RTLD_GLOBAL)
            print("Notice: CPU-only mode")
        else:
            # Try the other way, in case no_gpu was
            # compile but not renamed
            lib = CDLL(winGPUdll, RTLD_GLOBAL)
            print("Environment variables indicated a CPU run, but we didn't find `"+winNoGPUdll+"`. Trying a GPU run anyway.")
else:
    lib = CDLL("./libdarknet.so", RTLD_GLOBAL)
    lib = CDLL("./darknet.so", RTLD_GLOBAL)
lib.network_width.argtypes = [c_void_p]
lib.network_width.restype = c_int
lib.network_height.argtypes = [c_void_p]
@@ -160,6 +161,10 @@
load_net.argtypes = [c_char_p, c_char_p, c_int]
load_net.restype = c_void_p

load_net_custom = lib.load_network_custom
load_net_custom.argtypes = [c_char_p, c_char_p, c_int, c_int]
load_net_custom.restype = c_void_p

do_nms_obj = lib.do_nms_obj
do_nms_obj.argtypes = [POINTER(DETECTION), c_int, c_int, c_float]

@@ -188,6 +193,18 @@
predict_image.argtypes = [c_void_p, IMAGE]
predict_image.restype = POINTER(c_float)

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

def classify(net, meta, im):
    out = predict_image(net, im)
    res = []
@@ -206,6 +223,11 @@
    """
    #pylint: disable= C0321
    im = load_image(image, 0, 0)
    #import cv2
    #custom_image = cv2.imread(image) # use: detect(,,imagePath,)
    #import scipy.misc
    #custom_image = scipy.misc.imread(image)
    #im, arr = array_to_image(custom_image)     # you should comment line below: free_image(im)
    if debug: print("Loaded image")
    num = c_int(0)
    if debug: print("Assigned num")
@@ -253,7 +275,7 @@
metaMain = None
altNames = None

def performDetect(imagePath="data/dog.jpg", thresh= 0.25, configPath = "./yolov3.cfg", weightPath = "yolov3.weights", metaPath= "./data/coco.data", showImage= True, makeImageOnly = False, initOnly= False):
def performDetect(imagePath="data/dog.jpg", thresh= 0.25, configPath = "./cfg/yolov3.cfg", weightPath = "yolov3.weights", metaPath= "./data/coco.data", showImage= True, makeImageOnly = False, initOnly= False):
    """
    Convenience function to handle the detection and returns of objects.

@@ -310,7 +332,7 @@
    if not os.path.exists(metaPath):
        raise ValueError("Invalid data file path `"+os.path.abspath(metaPath)+"`")
    if netMain is None:
        netMain = load_net(configPath.encode("ascii"), weightPath.encode("ascii"), 0)
        netMain = load_net_custom(configPath.encode("ascii"), weightPath.encode("ascii"), 0, 1)  # batch size = 1
    if metaMain is None:
        metaMain = load_meta(metaPath.encode("ascii"))
    if altNames is None: