关于windows10+vs2017+cuda10.1+darknet编译出现问题,错误c2061,不知道怎么办了?

就编译运行daeknet.sln时,总是会出现这个问题,编译无法通过
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库目录,包含目录都添加了opencv和cuda10.1的目录,该链接的也连接了,也用的vs2015的开发工具,求大神解答啊,一直卡着!!!

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qq_43513349 博主,你解决了吗?
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qq_43513349
qq_43513349 博主,你解决了吗?
大约 2 个月之前 回复
qq_43513349
qq_43513349 博主,你解决了吗?
大约 2 个月之前 回复
qq_43513349
qq_43513349 博主,你解决了吗?
大约 2 个月之前 回复
qq_43513349
qq_43513349 博主,你解决了吗?
大约 2 个月之前 回复
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关于windows10+vs2017+cuda10.1+darknet编译出现问题,错误c2061,不知道怎么办了?

就编译运行daeknet.sln时,总是会出现这个问题,编译无法通过 ![图片说明](https://img-ask.csdn.net/upload/201903/06/1551859573_853219.png) ![图片说明](https://img-ask.csdn.net/upload/201903/06/1551859581_80181.png) 库目录,包含目录都添加了opencv和cuda10.1的目录,该链接的也连接了,也用的vs2015的开发工具,求大神解答啊,一直卡着!!!

安装YOLO的darknet编译出现问题

请教一下各位,就是我在下载darknet后编译出现了make: * [obj/convolutiona_l_layer.o] Error 1 的问题 ![图片说明](https://img-ask.csdn.net/upload/201701/14/1484380384_669825.png) cuda版本7.5 gcc版本7.5 opencv版本2.4.8 ubuntu版本14.04 希望大家能帮我解决一下,谢谢!

求救!darknet生成的时候报错,CUDA 8.0.targets(216,9): error : Item '..\..\src

目前环境是 win7 CUDA 8.0 cudnn-8.0-windows7 vs2015 截图: ![图片说明](https://img-ask.csdn.net/upload/201906/22/1561203495_152612.png) ![图片说明](https://img-ask.csdn.net/upload/201906/22/1561203537_735733.png) ![图片说明](https://img-ask.csdn.net/upload/201906/22/1561203544_325293.png) 原本我的环境是高版本的,但因为这个问题换了版本,依然是解决不了这个问题了,就差重装系统了,初入社区,没有什么C币,愿提供21款数据恢复软件+3款文件粉碎软件做为报酬,再次感谢

vs2017编译通过,提示却有错误,切换预览文件错误会消失和出现

cocos2dx使用vs2017编译出现错误(活动)严重性为abc的一推提示,但编译过了,切换预览文件错误会消失和出现,大多为 “std”不明确,"cocos2d"不明确,“cocos2d::std”不明确等等。![图片说明](https://img-ask.csdn.net/upload/201805/26/1527330565_456192.png)

求助 win10配置yolo,运行darknet.sln,编译器报错。

win10配置yolo,运行darknet.sln,编译器报了一堆奇奇怪怪的错误 cuda 10.0 opencv 3.4.1 vs2017 ![图片说明](https://img-ask.csdn.net/upload/201812/02/1543756187_755458.jpg)

VS2015+Opencv3.4.0配置无GPU下darknet环境编译出错

![图片说明](https://img-ask.csdn.net/upload/202004/07/1586252632_26621.png) 编译darknet-master->build->darknet->darknet_no_gpu.sln文件出现如下错误,已经按照相关教程在包含目录、库目录下修改为自己的opencv安装路径。也是在Release+x64平台下编译的。

在Autoware 中编译yolo3节点时,发生darknet: ./src/cuda.c:36: check_error: Assertio `0' failed.

在Autoware 中编译yolo3节点时,发生darknet: ./src/cuda.c:36: check_error: Assertio `0' failed. CUDA error:unknown error

使用darknet时出现的问题

./darknet detect ./cfg/tiny-yolo-voc.cfg tiny-yolo-voc.weights ./data/eagle.jpg 在我输入这条指令测试时冒出了 layer filters size input output 0 conv 32 3 x 3 / 1 416 x 416 x 3 -> 416 x 416 x 32 1 max 2 x 2 / 2 416 x 416 x 32 -> 208 x 208 x 32 2 conv 64 3 x 3 / 1 208 x 208 x 32 -> 208 x 208 x 64 3 max 2 x 2 / 2 208 x 208 x 64 -> 104 x 104 x 64 4 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 5 conv 64 1 x 1 / 1 104 x 104 x 128 -> 104 x 104 x 64 6 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 7 max 2 x 2 / 2 104 x 104 x 128 -> 52 x 52 x 128 8 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 9 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 10 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 11 max 2 x 2 / 2 52 x 52 x 256 -> 26 x 26 x 256 12 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 13 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 14 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 15 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 16 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 17 max 2 x 2 / 2 26 x 26 x 512 -> 13 x 13 x 512 18 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 19 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 20 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 21 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 22 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 23 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024 24 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024 25 route 16 26 conv 64 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 64 27 reorg / 2 26 x 26 x 64 -> 13 x 13 x 256 28 route 27 24 29 conv 1024 3 x 3 / 1 13 x 13 x1280 -> 13 x 13 x1024 30 conv 120 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 120 31 detection darknet: ./src/parser.c:280: parse_region: Assertion `l.outputs == params.inputs' failed. 已放弃 (核心已转储) 这样的提示 请问这个错误提示是因为什么呢? 另外我在安装完darknet之后按照csdn上的教程改参数,可是发现我的src文件夹中没有yolo.c等文件,但是example里面有,我就给拷贝到了scr中并做了修改,现在想想是不是安装失败了啊orz

YOLO的darknet make时出错

makefile里gpu和opencv=0。先是显示ofast无效的选项参数,后来注释掉了之后就显示darknet.h里有typedef‘network’重定义错误。很崩溃,跪求大佬

yolo3 darknet.py问题

我用darknetAB https://github.com/AlexeyAB/darknet 编译gpu版本后生成darknet.py文件 然后我也编译了yolo_cpp_dll.sln文件 生成dll文件 然后运行darknet.py文件 不显示图片 异常退出 ![图片说明](https://img-ask.csdn.net/upload/201911/02/1572688446_628910.png) 百度了这个问题 有人说要换python3.5版本 我也尝试了 但是也是不行 不会显示图片。请问各位大佬到底怎么解决??急!!!谢谢!!! ``` #!python3 """ Python 3 wrapper for identifying objects in images Requires DLL compilation Both the GPU and no-GPU version should be compiled; the no-GPU version should be renamed "yolo_cpp_dll_nogpu.dll". On a GPU system, you can force CPU evaluation by any of: - Set global variable DARKNET_FORCE_CPU to True - Set environment variable CUDA_VISIBLE_DEVICES to -1 - Set environment variable "FORCE_CPU" to "true" To use, either run performDetect() after import, or modify the end of this file. See the docstring of performDetect() for parameters. Directly viewing or returning bounding-boxed images requires scikit-image to be installed (`pip install scikit-image`) Original *nix 2.7: https://github.com/pjreddie/darknet/blob/0f110834f4e18b30d5f101bf8f1724c34b7b83db/python/darknet.py Windows Python 2.7 version: https://github.com/AlexeyAB/darknet/blob/fc496d52bf22a0bb257300d3c79be9cd80e722cb/build/darknet/x64/darknet.py @author: Philip Kahn @date: 20180503 """ #pylint: disable=R, W0401, W0614, W0703 from ctypes import * import math import random import os def sample(probs): s = sum(probs) probs = [a/s for a in probs] r = random.uniform(0, 1) for i in range(len(probs)): r = r - probs[i] if r <= 0: return i return len(probs)-1 def c_array(ctype, values): arr = (ctype*len(values))() arr[:] = values return arr class BOX(Structure): _fields_ = [("x", c_float), ("y", c_float), ("w", c_float), ("h", c_float)] class DETECTION(Structure): _fields_ = [("bbox", BOX), ("classes", c_int), ("prob", POINTER(c_float)), ("mask", POINTER(c_float)), ("objectness", c_float), ("sort_class", c_int)] class IMAGE(Structure): _fields_ = [("w", c_int), ("h", c_int), ("c", c_int), ("data", POINTER(c_float))] class METADATA(Structure): _fields_ = [("classes", c_int), ("names", POINTER(c_char_p))] #lib = CDLL("/home/pjreddie/documents/darknet/libdarknet.so", RTLD_GLOBAL) #lib = CDLL("libdarknet.so", RTLD_GLOBAL) hasGPU = True if os.name == "nt": 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: try: tmp = os.environ["FORCE_CPU"].lower() if tmp in ["1", "true", "yes", "on"]: raise ValueError("ForceCPU") else: print("Flag value '"+tmp+"' not forcing CPU mode") except KeyError: # We never set the flag if 'CUDA_VISIBLE_DEVICES' in envKeys: if int(os.environ['CUDA_VISIBLE_DEVICES']) < 0: raise ValueError("ForceCPU") try: 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") if not os.path.exists(winGPUdll): raise ValueError("NoDLL") lib = CDLL(winGPUdll, RTLD_GLOBAL) except (KeyError, ValueError): 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.network_width.argtypes = [c_void_p] lib.network_width.restype = c_int lib.network_height.argtypes = [c_void_p] lib.network_height.restype = c_int copy_image_from_bytes = lib.copy_image_from_bytes copy_image_from_bytes.argtypes = [IMAGE,c_char_p] def network_width(net): return lib.network_width(net) def network_height(net): return lib.network_height(net) predict = lib.network_predict_ptr predict.argtypes = [c_void_p, POINTER(c_float)] predict.restype = POINTER(c_float) if hasGPU: set_gpu = lib.cuda_set_device set_gpu.argtypes = [c_int] make_image = lib.make_image make_image.argtypes = [c_int, c_int, c_int] make_image.restype = IMAGE get_network_boxes = lib.get_network_boxes get_network_boxes.argtypes = [c_void_p, c_int, c_int, c_float, c_float, POINTER(c_int), c_int, POINTER(c_int), c_int] get_network_boxes.restype = POINTER(DETECTION) make_network_boxes = lib.make_network_boxes make_network_boxes.argtypes = [c_void_p] make_network_boxes.restype = POINTER(DETECTION) free_detections = lib.free_detections free_detections.argtypes = [POINTER(DETECTION), c_int] free_ptrs = lib.free_ptrs free_ptrs.argtypes = [POINTER(c_void_p), c_int] network_predict = lib.network_predict_ptr network_predict.argtypes = [c_void_p, POINTER(c_float)] reset_rnn = lib.reset_rnn reset_rnn.argtypes = [c_void_p] load_net = lib.load_network 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] do_nms_sort = lib.do_nms_sort do_nms_sort.argtypes = [POINTER(DETECTION), c_int, c_int, c_float] free_image = lib.free_image free_image.argtypes = [IMAGE] letterbox_image = lib.letterbox_image letterbox_image.argtypes = [IMAGE, c_int, c_int] letterbox_image.restype = IMAGE load_meta = lib.get_metadata lib.get_metadata.argtypes = [c_char_p] lib.get_metadata.restype = METADATA load_image = lib.load_image_color load_image.argtypes = [c_char_p, c_int, c_int] load_image.restype = IMAGE rgbgr_image = lib.rgbgr_image rgbgr_image.argtypes = [IMAGE] predict_image = lib.network_predict_image predict_image.argtypes = [c_void_p, IMAGE] predict_image.restype = POINTER(c_float) predict_image_letterbox = lib.network_predict_image_letterbox predict_image_letterbox.argtypes = [c_void_p, IMAGE] predict_image_letterbox.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 = [] for i in range(meta.classes): if altNames is None: nameTag = meta.names[i] else: nameTag = altNames[i] res.append((nameTag, out[i])) res = sorted(res, key=lambda x: -x[1]) return res def detect(net, meta, image, thresh=.5, hier_thresh=.5, nms=.45, debug= False): """ Performs the meat of the detection """ #pylint: disable= C0321 im = load_image(image, 0, 0) if debug: print("Loaded image") ret = detect_image(net, meta, im, thresh, hier_thresh, nms, debug) free_image(im) if debug: print("freed image") return ret def detect_image(net, meta, im, thresh=.5, hier_thresh=.5, nms=.45, debug= False): #import cv2 #custom_image_bgr = cv2.imread(image) # use: detect(,,imagePath,) #custom_image = cv2.cvtColor(custom_image_bgr, cv2.COLOR_BGR2RGB) #custom_image = cv2.resize(custom_image,(lib.network_width(net), lib.network_height(net)), interpolation = cv2.INTER_LINEAR) #import scipy.misc #custom_image = scipy.misc.imread(image) #im, arr = array_to_image(custom_image) # you should comment line below: free_image(im) num = c_int(0) if debug: print("Assigned num") pnum = pointer(num) if debug: print("Assigned pnum") predict_image(net, im) letter_box = 0 #predict_image_letterbox(net, im) #letter_box = 1 if debug: print("did prediction") # dets = get_network_boxes(net, custom_image_bgr.shape[1], custom_image_bgr.shape[0], thresh, hier_thresh, None, 0, pnum, letter_box) # OpenCV dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, None, 0, pnum, letter_box) if debug: print("Got dets") num = pnum[0] if debug: print("got zeroth index of pnum") if nms: do_nms_sort(dets, num, meta.classes, nms) if debug: print("did sort") res = [] if debug: print("about to range") for j in range(num): if debug: print("Ranging on "+str(j)+" of "+str(num)) if debug: print("Classes: "+str(meta), meta.classes, meta.names) for i in range(meta.classes): if debug: print("Class-ranging on "+str(i)+" of "+str(meta.classes)+"= "+str(dets[j].prob[i])) if dets[j].prob[i] > 0: b = dets[j].bbox if altNames is None: nameTag = meta.names[i] else: nameTag = altNames[i] if debug: print("Got bbox", b) print(nameTag) print(dets[j].prob[i]) print((b.x, b.y, b.w, b.h)) res.append((nameTag, dets[j].prob[i], (b.x, b.y, b.w, b.h))) if debug: print("did range") res = sorted(res, key=lambda x: -x[1]) if debug: print("did sort") free_detections(dets, num) if debug: print("freed detections") return res netMain = None metaMain = None altNames = None def performDetect(imagePath="data/dog.jpg", thresh= 0.25, configPath = "./cfg/yolov3.cfg", weightPath = "yolov3.weights", metaPath= "./cfg/coco.data", showImage= True, makeImageOnly = False, initOnly= False): """ Convenience function to handle the detection and returns of objects. Displaying bounding boxes requires libraries scikit-image and numpy Parameters ---------------- imagePath: str Path to the image to evaluate. Raises ValueError if not found thresh: float (default= 0.25) The detection threshold configPath: str Path to the configuration file. Raises ValueError if not found weightPath: str Path to the weights file. Raises ValueError if not found metaPath: str Path to the data file. Raises ValueError if not found showImage: bool (default= True) Compute (and show) bounding boxes. Changes return. makeImageOnly: bool (default= False) If showImage is True, this won't actually *show* the image, but will create the array and return it. initOnly: bool (default= False) Only initialize globals. Don't actually run a prediction. Returns ---------------------- When showImage is False, list of tuples like ('obj_label', confidence, (bounding_box_x_px, bounding_box_y_px, bounding_box_width_px, bounding_box_height_px)) The X and Y coordinates are from the center of the bounding box. Subtract half the width or height to get the lower corner. Otherwise, a dict with { "detections": as above "image": a numpy array representing an image, compatible with scikit-image "caption": an image caption } """ # Import the global variables. This lets us instance Darknet once, then just call performDetect() again without instancing again global metaMain, netMain, altNames #pylint: disable=W0603 assert 0 < thresh < 1, "Threshold should be a float between zero and one (non-inclusive)" if not os.path.exists(configPath): raise ValueError("Invalid config path `"+os.path.abspath(configPath)+"`") if not os.path.exists(weightPath): raise ValueError("Invalid weight path `"+os.path.abspath(weightPath)+"`") if not os.path.exists(metaPath): raise ValueError("Invalid data file path `"+os.path.abspath(metaPath)+"`") if netMain is None: 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: # In Python 3, the metafile default access craps out on Windows (but not Linux) # Read the names file and create a list to feed to detect try: with open(metaPath) as metaFH: metaContents = metaFH.read() import re match = re.search("names *= *(.*)$", metaContents, re.IGNORECASE | re.MULTILINE) if match: result = match.group(1) else: result = None try: if os.path.exists(result): with open(result) as namesFH: namesList = namesFH.read().strip().split("\n") altNames = [x.strip() for x in namesList] except TypeError: pass except Exception: pass if initOnly: print("Initialized detector") return None if not os.path.exists(imagePath): raise ValueError("Invalid image path `"+os.path.abspath(imagePath)+"`") # Do the detection #detections = detect(netMain, metaMain, imagePath, thresh) # if is used cv2.imread(image) detections = detect(netMain, metaMain, imagePath.encode("ascii"), thresh) if showImage: try: from skimage import io, draw import numpy as np image = io.imread(imagePath) print("*** "+str(len(detections))+" Results, color coded by confidence ***") imcaption = [] for detection in detections: label = detection[0] confidence = detection[1] pstring = label+": "+str(np.rint(100 * confidence))+"%" imcaption.append(pstring) print(pstring) bounds = detection[2] shape = image.shape # x = shape[1] # xExtent = int(x * bounds[2] / 100) # y = shape[0] # yExtent = int(y * bounds[3] / 100) yExtent = int(bounds[3]) xEntent = int(bounds[2]) # Coordinates are around the center xCoord = int(bounds[0] - bounds[2]/2) yCoord = int(bounds[1] - bounds[3]/2) boundingBox = [ [xCoord, yCoord], [xCoord, yCoord + yExtent], [xCoord + xEntent, yCoord + yExtent], [xCoord + xEntent, yCoord] ] # Wiggle it around to make a 3px border rr, cc = draw.polygon_perimeter([x[1] for x in boundingBox], [x[0] for x in boundingBox], shape= shape) rr2, cc2 = draw.polygon_perimeter([x[1] + 1 for x in boundingBox], [x[0] for x in boundingBox], shape= shape) rr3, cc3 = draw.polygon_perimeter([x[1] - 1 for x in boundingBox], [x[0] for x in boundingBox], shape= shape) rr4, cc4 = draw.polygon_perimeter([x[1] for x in boundingBox], [x[0] + 1 for x in boundingBox], shape= shape) rr5, cc5 = draw.polygon_perimeter([x[1] for x in boundingBox], [x[0] - 1 for x in boundingBox], shape= shape) boxColor = (int(255 * (1 - (confidence ** 2))), int(255 * (confidence ** 2)), 0) draw.set_color(image, (rr, cc), boxColor, alpha= 0.8) draw.set_color(image, (rr2, cc2), boxColor, alpha= 0.8) draw.set_color(image, (rr3, cc3), boxColor, alpha= 0.8) draw.set_color(image, (rr4, cc4), boxColor, alpha= 0.8) draw.set_color(image, (rr5, cc5), boxColor, alpha= 0.8) if not makeImageOnly: io.imshow(image) io.show() detections = { "detections": detections, "image": image, "caption": "\n<br/>".join(imcaption) } except Exception as e: print("Unable to show image: "+str(e)) return detections if __name__ == "__main__": print(performDetect()) ```

YOLO在python中调用设置darknet.set_gpu(1)无效

我的操作系统是macos,显卡为GT750M,已经成功安装了cuda,在终端调用yolo官网的示例代码可以实现gpu运算,但在python中按照作者封装好的darknet.py调用yolo时设置darknet.set_gpu(1)却无法使用gpu运算,仍是cpu运算。 我在/src/cuda.c中把cuda_set_device函数的gpu_index直接设置为1,仍无法使用gpu运算,我对c++了解的不是很多,希望大神可以帮我解决这个问题。

YOLO OSError: [WinError 126] 找不到指定的模块

由于毕设需要用到图像识别接触到了yolo,根据 https://blog.csdn.net/LutherK/article/details/80151514 博主的内容照着做,运行发现报错 F:\python\python.exe F:/VS2017/darknet-master/python/my_local_video_darknet.py Traceback (most recent call last): File "F:/VS2017/darknet-master/python/my_local_video_darknet.py", line 56, in <module> lib = CDLL("F:/VS2017/darknet-master/libdarknet.so", RTLD_GLOBAL) File "F:\python\lib\ctypes\__init__.py", line 348, in __init__ self._handle = _dlopen(self._name, mode) OSError: [WinError 126] 找不到指定的模块。 在网上找了很久也没有头绪,不知道该如何解决,还请各位帮忙,谢谢。自己的python版本是3.7,参考博主的python是2.7,不知道是不是版本差异的问题。

AlexeyAB darknet 怎么用GPU训练?

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请问这个是CUDA没有配置好吗

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CUDA错误 __global__ funtion call

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在Win10 VS2015下配置opencv3.3出问题

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'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\msvcp140d.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\opencv_world330.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\ucrtbased.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\user32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\gdi32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\win32u.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\gdi32full.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\ole32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\combase.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\oleaut32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\ucrtbase.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\msvcp_win.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\rpcrt4.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\comdlg32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\msvcrt.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\bcryptprimitives.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\sechost.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\SHCore.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\advapi32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\shlwapi.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\shell32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\msvfw32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\avicap32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\avifil32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\cfgmgr32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\winmm.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\winmmbase.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\windows.storage.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\powrprof.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\concrt140d.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\WinSxS\amd64_microsoft.windows.common-controls_6595b64144ccf1df_5.82.14393.447_none_0d5aa7fbb6d35646\comctl32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\WinSxS\amd64_microsoft.windows.common-controls_6595b64144ccf1df_5.82.14393.447_none_0d5aa7fbb6d35646\comctl32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\kernel.appcore.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\profapi.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\msacm32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Unloaded 'C:\Windows\WinSxS\amd64_microsoft.windows.common-controls_6595b64144ccf1df_5.82.14393.447_none_0d5aa7fbb6d35646\comctl32.dll' 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\msvcp140.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\vcruntime140.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\concrt140.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\imm32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\uxtheme.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\msctf.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\dwmapi.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\OpenCL.DLL'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\DriverStore\FileRepository\igdlh64.inf_amd64_e1474e9d5907af3f\IntelOpenCL64.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Program Files (x86)\Common Files\Intel\OpenCL\bin\x64\intelocl64.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\opengl32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Program Files (x86)\Common Files\Intel\OpenCL\bin\x64\task_executor64.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\ddraw.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\dciman32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\glu32.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Program Files (x86)\Common Files\Intel\OpenCL\bin\x64\cpu_device64.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\version.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\DriverStore\FileRepository\igdlh64.inf_amd64_e1474e9d5907af3f\igdrcl64.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\dxgi.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\ResourcePolicyClient.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Unloaded 'C:\Windows\System32\ResourcePolicyClient.dll' 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\DriverStore\FileRepository\igdlh64.inf_amd64_e1474e9d5907af3f\igdfcl64.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\DriverStore\FileRepository\igdlh64.inf_amd64_e1474e9d5907af3f\igdmcl64.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\dbghelp.dll'. Cannot find or open the PDB file. 'computer vision1.exe' (Win32): Loaded 'C:\Windows\System32\DriverStore\FileRepository\igdlh64.inf_amd64_e1474e9d5907af3f\igc64.dll'. Cannot find or open the PDB file. The thread 0x1cd4 has exited with code 0 (0x0). The thread 0x1750 has exited with code 0 (0x0). The thread 0x3668 has exited with code 0 (0x0). The thread 0x2b88 has exited with code 0 (0x0). The program '[6504] computer vision1.exe' has exited with code 0 (0x0).

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