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yolo with opencv error

I am trying to yolo in opencv but getting the error

CODE IS BELOW

import cv2 import numpy as np import time

Load Yolo

net = cv2.dnn.readNet("weights/yolov3-tiny.weights", "cfg/yolov3-tiny.cfg") classes = [] with open("coco.names", "r") as f: classes = [line.strip() for line in f.readlines()] layer_names = net.getLayerNames() output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()] colors = np.random.uniform(0, 255, size=(len(classes), 3))

Loading image

cap = cv2.VideoCapture(0)

font = cv2.FONT_HERSHEY_PLAIN starting_time = time.time() frame_id = 0 while True: _, frame = cap.read() frame_id += 1

height, width, channels = frame.shape

# Detecting objects
blob = cv2.dnn.blobFromImage(frame, 0.00392, (416, 416), (0, 0, 0), True, crop=False)

net.setInput(blob)
outs = net.forward(output_layers)

# Showing informations on the screen
class_ids = []
confidences = []
boxes = []
for out in outs:
    for detection in out:
        scores = detection[5:]
        class_id = np.argmax(scores)
        confidence = scores[class_id]
        if confidence > 0.2:
            # Object detected
            center_x = int(detection[0] * width)
            center_y = int(detection[1] * height)
            w = int(detection[2] * width)
            h = int(detection[3] * height)

            # Rectangle coordinates
            x = int(center_x - w / 2)
            y = int(center_y - h / 2)

            boxes.append([x, y, w, h])
            confidences.append(float(confidence))
            class_ids.append(class_id)

indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.8, 0.3)

for i in range(len(boxes)):
    if i in indexes:
        x, y, w, h = boxes[i]
        label = str(classes[class_ids[i]])
        confidence = confidences[i]
        color = colors[class_ids[i]]
        cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
        cv2.putText(frame, label + " " + str(round(confidence, 2)), (x, y + 30), font, 3, color, 3)



elapsed_time = time.time() - starting_time
fps = frame_id / elapsed_time
cv2.putText(frame, "FPS: " + str(round(fps, 2)), (10, 50), font, 4, (0, 0, 0), 3)
cv2.imshow("Image", frame)
key = cv2.waitKey(1)
if key == 27:
    break

cap.release() cv2.destroyAllWindows()

ERROR

Traceback (most recent call last): File "C:\Users\iamfa\Desktop\yolo_realtime_detection_cpu\real_time_yolo.py", line 6, in <module> net = cv2.dnn.readNet("weights/yolov3-tiny.weights", "cfg/yolov3-tiny.cfg") cv2.error: OpenCV(4.1.2) C:\projects\opencv-python\opencv\modules\dnn\src\darknet\darknet_importer.cpp:214: error: (-212:Parsing error) Failed to parse NetParameter file: weights/yolov3-tiny.weights in function 'cv::dnn::dnn4_v20190902::readNetFromDarknet'

[Finished in 0.9s]

yolo with opencv error

I am trying to yolo in opencv but getting the ~~error~~

error CODE IS BELOW

import cv2 import numpy as np import time time # Load Yolo Yolo net = cv2.dnn.readNet("weights/yolov3-tiny.weights", "cfg/yolov3-tiny.cfg") classes = [] with open("coco.names", "r") as f: classes = [line.strip() for line in f.readlines()] layer_names = net.getLayerNames() output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()] colors = np.random.uniform(0, 255, size=(len(classes), 3)) 3)) # Loading image image cap = cv2.VideoCapture(0) cv2.VideoCapture(0) font = cv2.FONT_HERSHEY_PLAIN starting_time = time.time() frame_id = 0 while True: _, frame = cap.read() frame_id += 1 1 height, width, channels = frame.shape # Detecting objects blob = cv2.dnn.blobFromImage(frame, 0.00392, (416, 416), (0, 0, 0), True, crop=False) net.setInput(blob) outs = net.forward(output_layers) # Showing informations on the screen class_ids = [] confidences = [] boxes = [] for out in outs: for detection in out: scores = detection[5:] class_id = np.argmax(scores) confidence = scores[class_id] if confidence > 0.2: # Object detected center_x = int(detection[0] * width) center_y = int(detection[1] * height) w = int(detection[2] * width) h = int(detection[3] * height) # Rectangle coordinates x = int(center_x - w / 2) y = int(center_y - h / 2) boxes.append([x, y, w, h]) confidences.append(float(confidence)) class_ids.append(class_id) indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.8, 0.3) for i in range(len(boxes)): if i in indexes: x, y, w, h = boxes[i] label = str(classes[class_ids[i]]) confidence = confidences[i] color = colors[class_ids[i]] cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2) cv2.putText(frame, label + " " + str(round(confidence, 2)), (x, y + 30), font, 3, color, 3) elapsed_time = time.time() - starting_time fps = frame_id / elapsed_time cv2.putText(frame, "FPS: " + str(round(fps, 2)), (10, 50), font, 4, (0, 0, 0), 3) cv2.imshow("Image", frame) key = cv2.waitKey(1) if key == 27: break cap.release() cv2.destroyAllWindows() cap.release() cv2.destroyAllWindows()ERROR ERROR Traceback (most recent call last): File "C:\Users\iamfa\Desktop\yolo_realtime_detection_cpu\real_time_yolo.py", line 6, in <module> net = cv2.dnn.readNet("weights/yolov3-tiny.weights", "cfg/yolov3-tiny.cfg") cv2.error: OpenCV(4.1.2) C:\projects\opencv-python\opencv\modules\dnn\src\darknet\darknet_importer.cpp:214: error: (-212:Parsing error) Failed to parse NetParameter file: weights/yolov3-tiny.weights in function 'cv::dnn::dnn4_v20190902::readNetFromDarknet' 'cv::dnn::dnn4_v20190902::readNetFromDarknet' [Finished in 0.9s]0.9s]