# Overload resolution failed

**URL:** <https://forum.opencv.org/t/overload-resolution-failed/16346>\
**Category:** Python\
**Tags:** programming\
**Created:** [February 2, 2024, 8:42am UTC](https://forum.opencv.org/t/overload-resolution-failed/16346 "2024-02-02T08:42:21Z")\
**Posts on this page:** 6\
**Page:** 1

<div class="post-metadata">

**Author:** ![ivercool](https://avatars.discourse-cdn.com/v4/letter/i/779978/32.png) [@ivercool](https://forum.opencv.org/u/ivercool)\
**Post date:** [February 2, 2024, 8:42am UTC](https://forum.opencv.org/t/overload-resolution-failed/16346/1 "2024-02-02T08:42:22Z")

</div>

I am trying to implement a face detection using openCV. However, I encountered an error on this line of code:

```python
cv2.rectangle(frame, (left,top), (right,bottom), (0,255,0), 2)

```

```none
cv2.error: OpenCV(4.5.2) : error: (-5:Bad argument) in function 'rectangle'> Overload resolution failed:

* Can't parse 'pt1'. Sequence item with index 0 has a wrong type
* Can't parse 'pt1'. Sequence item with index 0 has a wrong type
* Can't parse 'rec'. Expected sequence length 4, got 2
* Can't parse 'rec'. Expected sequence length 4, got 2

```

Here is the code that I am working on

```python
import numpy as np
import cv2

def nms_boxes(boxes, scores, nms_threshold):
   
    x1 = boxes[:, 0]
    y1 = boxes[:, 1]
    x2 = boxes[:, 2]
    y2 = boxes[:, 3]

    areas = (x2-x1+1)*(y2-y1+1)
    order = scores.argsort()[::-1]

    keep = []
    while order.size > 0:
        i = order[0]
        keep.append(i)

        xx1 = np.maximum(x1[i], x1[order[1:]])
        yy1 = np.maximum(y1[i], y1[order[1:]])
        xx2 = np.minimum(x2[i], x2[order[1:]])
        yy2 = np.minimum(y2[i], y2[order[1:]])

        w1 = np.maximum(0.0, xx2 - xx1 + 1)
        h1 = np.maximum(0.0, yy2 - yy1 + 1)
        inter = w1 * h1

        ovr = inter / (areas[i] + areas[order[1:]] - inter)
        inds = np.where(ovr <= nms_threshold)[0] # threshold
        order = order[inds + 1]

    return keep

def softmax_2(data):    
    data_exp = np.zeros(data.shape)
    data_sum = np.zeros(data.shape)
    result = np.zeros(data.shape)
    data_exp = np.exp(data)
    data_sum[:,0] = np.sum(data_exp, axis=1)
    data_sum[:,1] = data_sum[:,0]
    result = data_exp / data_sum
    return result

class FaceDetect():  
  def __init__ (self, dpu, detThreshold=0.55, nmsThreshold=0.35):
    self.detThreshold = detThreshold
    self.nmsThreshold = nmsThreshold

    self.inputChannels = []
    self.inputHeight = []
    self.inputWidth = []
    self.inputShape = []
    self.output0Channels = []
    self.output0Height = []
    self.output0Width = []
    self.output0Size = []
    self.output0Shape = []

  def config(self, detThreshold, nmsThreshold):
    self.detThreshold = detThreshold
    self.nmsThreshold = nmsThreshold
    
  def process(self,img):

    dpu = self.dpu
   
    inputHeight = self.inputHeight
    inputWidth = self.inputWidth
    inputShape = self.inputShape
    output0Height = self.output0Height
    output0Width = self.output0Width
    output0Size = self.output0Size
    output0Shape = self.output0Shape
    output1Size = self.output1Size
    output1Shape = self.output1Shape

    imgHeight = img.shape[0]
    imgWidth = img.shape[1]
    scale_h = imgHeight / inputHeight
    scale_w = imgWidth / inputWidth
    
    """ Image pre-processing """
    # normalize
    img = img - 128.0
    # resize
    img = cv2.resize(img,(inputWidth,inputHeight))

    """ Prepare input/output buffers """
    #print("[INFO] process - prep input buffer ")
    inputData = []
    inputData.append(np.empty((inputShape),dtype=np.float32,order='C'))
    inputImage = inputData[0]
    inputImage[0,...] = img

    #print("[INFO] process - prep output buffer ")
    outputData = []
    outputData.append(np.empty((output0Shape),dtype=np.float32,order='C'))
    outputData.append(np.empty((output1Shape),dtype=np.float32,order='C'))

    """ Execute model on DPU """
    job_id = dpu.execute_async( inputData, outputData )
    dpu.wait(job_id)

    """ Retrieve output results """    
    
    OutputData0 = outputData[0].reshape(1,output0Size)
    bboxes = np.reshape( OutputData0, (-1, 4) )
    #
    outputData1 = outputData[1].reshape(1,output1Size)
    scores = np.reshape( outputData1, (-1, 2))

    """ Get original face boxes """
    gy = np.arange(0,output0Height)
    gx = np.arange(0,output0Width)
    [x,y] = np.meshgrid(gx,gy)
    x = x.ravel()*4
    y = y.ravel()*4
    bboxes[:,0] = bboxes[:,0] + x
    bboxes[:,1] = bboxes[:,1] + y
    bboxes[:,2] = bboxes[:,2] + x
    bboxes[:,3] = bboxes[:,3] + y

    """ Run softmax """
    softmax = softmax_2( scores )

    """ Only keep faces for which prob is above detection threshold """
    prob = softmax[:,1] 
    keep_idx = prob.ravel() > self.detThreshold
    bboxes = bboxes[keep_idx, :]
    bboxes = np.array( bboxes, dtype=np.float32 )
    prob = prob[keep_idx]
	
    """ Perform Non-Maxima Suppression """
    face_indices = []
    if ( len(bboxes) > 0 ):
        face_indices = nms_boxes( bboxes, prob, self.nmsThreshold );
    faces = bboxes[face_indices]
    # extract bounding box for each face
    for i, face in enumerate(faces):
        xmin = max(face[0] * scale_w, 0 )
        ymin = max(face[1] * scale_h, 0 )
        xmax = min(face[2] * scale_w, imgWidth )
        ymax = min(face[3] * scale_h, imgHeight )
        faces[i] = ( int(xmin),int(ymin),int(xmax),int(ymax) )
    return faces
  # Initialize face detector
densebox_xmodel = "densebox_640_360.xmodel"
densebox_graph = xir.Graph.deserialize(densebox_xmodel)
dpu_face_detector = FaceDetect(densebox_dpu,detThreshold,nmsThreshold)
dpu_face_detector.start()

# Initialize the camera input
print("[INFO] starting camera input ...")
cam = cv2.VideoCapture(0)
cam.set(cv2.CAP_PROP_FRAME_WIDTH,640)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,480)
if not (cam.isOpened()):
    print("[ERROR] Failed to open camera ", 0)
    exit()

# loop over the frames from the video stream
while True:
	# Capture image from camera
	ret,frame = cam.read()

	# Vitis-AI/DPU based face detector
	faces = dpu_face_detector.process(frame)

	# loop over the faces
	for i,(left,top,right,bottom) in enumerate(faces): 
		# draw a bounding box surrounding the object so we can
		# visualize it
		cv2.rectangle( frame, (left,top), (right,bottom), (0,255,0), 2)
	# Display the processed image
	cv2.imshow("Face Detection", frame)
	key = cv2.waitKey(1) & 0xFF

	# if the `q` key was pressed, break from the loop
	if key == ord("q"):
		break
# Stop the face detector
dpu_face_detector.stop()
del densebox_dpu

# Cleanup
cam.release()
cv2.destroyAllWindows()

```

---

<div class="post-metadata">

**Author:** ![crackwitz](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.opencv.org/crackwitz/32/14_2.png) [@crackwitz](https://forum.opencv.org/u/crackwitz)\
**Post date:** [February 2, 2024, 4:04pm UTC](https://forum.opencv.org/t/overload-resolution-failed/16346/2 "2024-02-02T16:04:32Z")

</div>

what version of opencv?

---

<div class="post-metadata">

**Author:** ![ivercool](https://avatars.discourse-cdn.com/v4/letter/i/779978/32.png) [@ivercool](https://forum.opencv.org/u/ivercool)\
**Post date:** [February 2, 2024, 10:31pm UTC](https://forum.opencv.org/t/overload-resolution-failed/16346/4 "2024-02-02T22:31:32Z")

</div>

opencv version 4.5.2

---

<div class="post-metadata">

**Author:** ![crackwitz](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.opencv.org/crackwitz/32/14_2.png) [@crackwitz](https://forum.opencv.org/u/crackwitz)\
**Post date:** [February 3, 2024, 8:29am UTC](https://forum.opencv.org/t/overload-resolution-failed/16346/5 "2024-02-03T08:29:58Z")

</div>

oh right, says so right in the error message.

anyway, please update, then try again.

either that or check the type of those variables and report back.

---

<div class="post-metadata">

**Author:** ![berak](https://avatars.discourse-cdn.com/v4/letter/b/85f322/32.png) [@berak](https://forum.opencv.org/u/berak)\
**Post date:** [February 3, 2024, 9:13am UTC](https://forum.opencv.org/t/overload-resolution-failed/16346/6 "2024-02-03T09:13:36Z")

</div>

> [@ivercool](#):
>
> `faces[i] = ( int(xmin),int(ymin),int(xmax),int(ymax) )`

this line does not do, what you expected:

you’re trying to re-assign INTs to a float array, but python will copy the values AS FLOAT,  
it will NOT convert the array type.  
so, when you’re trying to pull them out again later, – still float, not int !  
(so they’re not acceptable for cv2.rectangle())

please, in the future, DEBUG YOUR PROBLEM !

- print out values & `type()`
- learn to use python’s debugger: `python -m pdb my.py`

---

<div class="post-metadata">

**Author:** ![ivercool](https://avatars.discourse-cdn.com/v4/letter/i/779978/32.png) [@ivercool](https://forum.opencv.org/u/ivercool)\
**Post date:** [February 3, 2024, 9:55pm UTC](https://forum.opencv.org/t/overload-resolution-failed/16346/7 "2024-02-03T21:55:03Z")

</div>

@berak I make a change to the code by casting those values to integer: cv2.rectangle(frame, (int(left) , int(top)), (int(right) , int(bottom)), (0,255,0), 2). It works now but instead of getting one rectangle frame, I get multiple rectangles overlapping each others.

\*\*Update: I get it working now. Thanks guys.