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fixed typo across the project

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This commit is contained in:
esimov
2020-10-21 11:03:06 +03:00
parent c85c33ef2f
commit 6b4129f4c8
17 changed files with 79 additions and 79 deletions
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2
core/flploc_test.go
View File

@@ -153,7 +153,7 @@ func TestFlploc_LandmarkPointsDetectorShouldReturnCorrectDetectionPoints(t *test
}
}
expectedLandmarkPoints := 2*len(eyeCascades) + len(mouthCascades) + 1
expectedLandmarkPoints := 2*len(eyeCascades) + len(mouthCascades) + 1 // lendmark points of the left/right eyes, mouth + nose
if expectedLandmarkPoints != detectedLandmarkPoints {
t.Fatalf("expected facial landmark points to be detected: %d, got: %d", expectedLandmarkPoints, detectedLandmarkPoints)
}

2
examples/blinkdet/blinkdet.go
View File

@@ -59,7 +59,7 @@ func FindFaces(pixels []uint8) uintptr {
coords := make([]int, 0, len(dets))
go func() {
// Since in Go we cannot transfer a 2d array trough an array pointer
// Since in Go we cannot transfer a 2d array through an array pointer
// we have to transform it into 1d array.
for _, v := range dets {
coords = append(coords, v...)

42
examples/blinkdet/blinkdet.py
View File

@@ -22,20 +22,20 @@ class GoPixelSlice(Structure):
("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
]
# Obtain the camera pixels and transfer them to Go trough C types.
# Obtain the camera pixels and transfer them to Go through C types.
def process_frame(pixs):
dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
# call FindFaces
faces = GoPixelSlice(pixels, len(pixs), len(pixs))
pigo.FindFaces.argtypes = [GoPixelSlice]
pigo.FindFaces.restype = c_void_p
# Call the exported FindFaces function from Go.
# Call the exported FindFaces function from Go.
ndets = pigo.FindFaces(faces)
data_pointer = cast(ndets, POINTER((c_longlong * ARRAY_DIM) * MAX_NDETS))
if data_pointer :
buffarr = ((c_longlong * ARRAY_DIM) * MAX_NDETS).from_address(addressof(data_pointer.contents))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, 5,))
@@ -54,7 +54,7 @@ cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
# Changing the camera resolution introduce a short delay in the camera initialization.
# Changing the camera resolution introduce a short delay in the camera initialization.
# For this reason we should delay the object detection process with a few milliseconds.
time.sleep(0.4)
@@ -77,9 +77,9 @@ while(True):
for det in dets:
if det[4] == 1: # 1 == face; 0 == pupil
face_posy = det[1]
cv2.rectangle(frame,
(int(det[1])-int(det[2]/2), int(det[0])-int(det[2]/2)),
(int(det[1])+int(det[2]/2), int(det[0])+int(det[2]/2)),
cv2.rectangle(frame,
(int(det[1])-int(det[2]/2), int(det[0])-int(det[2]/2)),
(int(det[1])+int(det[2]/2), int(det[0])+int(det[2]/2)),
(0, 0, 255), 2
)
else:
@@ -89,22 +89,22 @@ while(True):
x1, x2 = int(det[0])-int(det[2]*1.2), int(det[0])+int(det[2]*1.2)
y1, y2 = int(det[1])-int(det[2]*1.2), int(det[1])+int(det[2]*1.2)
subimg = frame[x1:x2, y1:y2]
subimg = frame[x1:x2, y1:y2]
if subimg is not None:
gray = cv2.cvtColor(subimg, cv2.COLOR_BGR2GRAY)
img_blur = cv2.medianBlur(gray, 1)
if img_blur is not None:
max_radius = int(det[2]*0.45)
circles = cv2.HoughCircles(img_blur, cv2.HOUGH_GRADIENT, 1, int(det[2]*0.45),
circles = cv2.HoughCircles(img_blur, cv2.HOUGH_GRADIENT, 1, int(det[2]*0.45),
param1=60, param2=21, minRadius=4, maxRadius=max_radius)
if circles is not None:
circles = np.uint16(np.around(circles))
for i in circles[0, :]:
if i[2] < max_radius and i[2] > 0:
# Draw outer circle
if i[2] < max_radius and i[2] > 0:
# Draw outer circle
cv2.circle(frame, (int(det[1]), int(det[0])), i[2], (0, 255, 0), 2)
# Draw inner circle
cv2.circle(frame, (int(det[1]), int(det[0])), 2, (255, 0, 255), 3)
@@ -112,21 +112,21 @@ while(True):
if face_posy < y1:
count_left = 0
else:
count_right = 0
if count_left < EYE_CLOSED_CONSEC_FRAMES:
count_right = 0
if count_left < EYE_CLOSED_CONSEC_FRAMES:
cv2.putText(frame, "Left blink!", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
elif count_right < EYE_CLOSED_CONSEC_FRAMES:
cv2.putText(frame, "Right blink!", (frame.shape[1]-150, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.circle(frame, (int(det[1]), int(det[0])), 4, (0, 0, 255), -1, 8, 0)
if show_eyes:
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
(0, 255, 0), 2
)

10
examples/facedet/demo.py
View File

@@ -19,20 +19,20 @@ class GoPixelSlice(Structure):
("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
]
# Obtain the camera pixels and transfer them to Go trough Ctypes.
# Obtain the camera pixels and transfer them to Go through Ctypes.
def process_frame(pixs):
dets = np.zeros(3 * MAX_NDETS, dtype=np.float32)
pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
# call FindFaces
faces = GoPixelSlice(pixels, len(pixs), len(pixs))
pigo.FindFaces.argtypes = [GoPixelSlice]
pigo.FindFaces.restype = c_void_p
# Call the exported FindFaces function from Go.
# Call the exported FindFaces function from Go.
ndets = pigo.FindFaces(faces)
data_pointer = cast(ndets, POINTER((c_longlong * 3) * MAX_NDETS))
if data_pointer :
buffarr = ((c_longlong * 3) * MAX_NDETS).from_address(addressof(data_pointer.contents))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, 3,))
@@ -49,7 +49,7 @@ cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
# Changing the camera resolution introduce a short delay in the camera initialization.
# Changing the camera resolution introduce a short delay in the camera initialization.
# For this reason we should delay the object detection process with a few milliseconds.
time.sleep(0.4)

10
examples/facedet/faceblur.py
View File

@@ -19,20 +19,20 @@ class GoPixelSlice(Structure):
("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
]
# Obtain the camera pixels and transfer them to Go trough Ctypes.
# Obtain the camera pixels and transfer them to Go through Ctypes.
def process_frame(pixs):
dets = np.zeros(3 * MAX_NDETS, dtype=np.float32)
pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
# call FindFaces
faces = GoPixelSlice(pixels, len(pixs), len(pixs))
pigo.FindFaces.argtypes = [GoPixelSlice]
pigo.FindFaces.restype = c_void_p
# Call the exported FindFaces function from Go.
# Call the exported FindFaces function from Go.
ndets = pigo.FindFaces(faces)
data_pointer = cast(ndets, POINTER((c_longlong * 3) * MAX_NDETS))
if data_pointer :
buffarr = ((c_longlong * 3) * MAX_NDETS).from_address(addressof(data_pointer.contents))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, 3,))
@@ -50,7 +50,7 @@ cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
# Changing the camera resolution introduce a short delay in the camera initialization.
# Changing the camera resolution introduce a short delay in the camera initialization.
# For this reason we should delay the object detection process with a few milliseconds.
time.sleep(0.4)

2
examples/facedet/pigo.go
View File

@@ -34,7 +34,7 @@ func FindFaces(pixels []uint8) uintptr {
det := make([]int, 0, len(result))
go func() {
// Since in Go we cannot transfer a 2d array trough an array pointer
// Since in Go we cannot transfer a 2d array through an array pointer
// we have to transform it into 1d array.
for _, v := range result {
det = append(det, v...)

2
examples/facial_landmark/flploc.go
View File

@@ -95,7 +95,7 @@ func FindFaces(pixels []uint8) uintptr {
coords := make([]int, 0, len(dets))
go func() {
// Since in Go we cannot transfer a 2d array trough an array pointer
// Since in Go we cannot transfer a 2d array through an array pointer
// we have to transform it into 1d array.
for _, v := range dets {
coords = append(coords, v...)

24
examples/facial_landmark/flploc.py
View File

@@ -20,20 +20,20 @@ class GoPixelSlice(Structure):
("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
]
# Obtain the camera pixels and transfer them to Go trough Ctypes.
# Obtain the camera pixels and transfer them to Go through Ctypes.
def process_frame(pixs):
dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
# call FindFaces
faces = GoPixelSlice(pixels, len(pixs), len(pixs))
pigo.FindFaces.argtypes = [GoPixelSlice]
pigo.FindFaces.restype = c_void_p
# Call the exported FindFaces function from Go.
# Call the exported FindFaces function from Go.
ndets = pigo.FindFaces(faces)
data_pointer = cast(ndets, POINTER((c_longlong * ARRAY_DIM) * MAX_NDETS))
if data_pointer :
buffarr = ((c_longlong * ARRAY_DIM) * MAX_NDETS).from_address(addressof(data_pointer.contents))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, ARRAY_DIM,))
@@ -42,7 +42,7 @@ def process_frame(pixs):
dets_len = res[0][0]
res = np.delete(res, 0, 0) # delete the first element from the array
# We have to multiply the detection length with the total
# We have to multiply the detection length with the total
# detection points(face, pupils and facial lendmark points), in total 18
dets = list(res.reshape(-1, ARRAY_DIM))[0:dets_len*18]
return dets
@@ -52,7 +52,7 @@ cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
# Changing the camera resolution introduce a short delay in the camera initialization.
# Changing the camera resolution introduce a short delay in the camera initialization.
# For this reason we should delay the object detection process with a few milliseconds.
time.sleep(0.4)
@@ -74,18 +74,18 @@ while(True):
for det in dets:
if det[3] > 50:
if det[4] == 0: # 0 == face;
cv2.rectangle(frame,
(int(det[1])-int(det[2]/2), int(det[0])-int(det[2]/2)),
(int(det[1])+int(det[2]/2), int(det[0])+int(det[2]/2)),
cv2.rectangle(frame,
(int(det[1])-int(det[2]/2), int(det[0])-int(det[2]/2)),
(int(det[1])+int(det[2]/2), int(det[0])+int(det[2]/2)),
(0, 0, 255), 2
)
elif det[4] == 1: # 1 == pupil;
if showPupil:
cv2.circle(frame, (int(det[1]), int(det[0])), 4, (0, 0, 255), -1, 8, 0)
if showEyes:
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
(0, 255, 255), 2
)
elif det[4] == 2: # 2 == facial landmark;

2
examples/puploc/puploc.go
View File

@@ -59,7 +59,7 @@ func FindFaces(pixels []uint8) uintptr {
coords := make([]int, 0, len(dets))
go func() {
// Since in Go we cannot transfer a 2d array trough an array pointer
// Since in Go we cannot transfer a 2d array through an array pointer
// we have to transform it into 1d array.
for _, v := range dets {
coords = append(coords, v...)

16
examples/puploc/puploc.py
View File

@@ -20,20 +20,20 @@ class GoPixelSlice(Structure):
("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
]
# Obtain the camera pixels and transfer them to Go trough Ctypes.
# Obtain the camera pixels and transfer them to Go through Ctypes.
def process_frame(pixs):
dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
# call FindFaces
faces = GoPixelSlice(pixels, len(pixs), len(pixs))
pigo.FindFaces.argtypes = [GoPixelSlice]
pigo.FindFaces.restype = c_void_p
# Call the exported FindFaces function from Go.
# Call the exported FindFaces function from Go.
ndets = pigo.FindFaces(faces)
data_pointer = cast(ndets, POINTER((c_longlong * ARRAY_DIM) * MAX_NDETS))
if data_pointer :
buffarr = ((c_longlong * ARRAY_DIM) * MAX_NDETS).from_address(addressof(data_pointer.contents))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, ARRAY_DIM,))
@@ -52,7 +52,7 @@ cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
# Changing the camera resolution introduce a short delay in the camera initialization.
# Changing the camera resolution introduce a short delay in the camera initialization.
# For this reason we should delay the object detection process with a few milliseconds.
time.sleep(0.4)
@@ -78,9 +78,9 @@ while(True):
if showPupil:
cv2.circle(frame, (int(det[1]), int(det[0])), 4, (0, 0, 255), -1, 8, 0)
if showEyes:
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
(0, 255, 0), 2
)

2
examples/puploc_masquerade/puploc.go
View File

@@ -70,7 +70,7 @@ func FindFaces(pixels []uint8) uintptr {
coords := make([]int, 0, len(dets))
go func() {
// Since in Go we cannot transfer a 2d array trough an array pointer
// Since in Go we cannot transfer a 2d array through an array pointer
// we have to transform it into 1d array.
for _, v := range dets {
coords = append(coords, v...)

28
examples/puploc_masquerade/puploc.py
View File

@@ -34,20 +34,20 @@ def rotateImage(image, angle):
return result
# Obtain the camera pixels and transfer them to Go trough Ctypes.
# Obtain the camera pixels and transfer them to Go through Ctypes.
def process_frame(pixs):
dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
# call FindFaces
faces = GoPixelSlice(pixels, len(pixs), len(pixs))
pigo.FindFaces.argtypes = [GoPixelSlice]
pigo.FindFaces.restype = c_void_p
# Call the exported FindFaces function from Go.
# Call the exported FindFaces function from Go.
ndets = pigo.FindFaces(faces)
data_pointer = cast(ndets, POINTER((c_longlong * ARRAY_DIM) * MAX_NDETS))
if data_pointer :
buffarr = ((c_longlong * ARRAY_DIM) * MAX_NDETS).from_address(addressof(data_pointer.contents))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, ARRAY_DIM,))
@@ -66,7 +66,7 @@ cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
# Changing the camera resolution introduce a short delay in the camera initialization.
# Changing the camera resolution introduce a short delay in the camera initialization.
# For this reason we should delay the object detection process with a few milliseconds.
time.sleep(0.4)
@@ -81,7 +81,7 @@ while(True):
if dets is not None:
# We know that the detected faces are taking place in the first positions of the multidimensional array.
for row, col, scale, q, angle in dets:
for row, col, scale, q, angle in dets:
if q > 50:
if angle == 0:
px, py = col, row
@@ -105,8 +105,8 @@ while(True):
# Convert the image to BGR
source_img = source_img[:,:,:3]
if scale < img_height or scale < img_width:
if img_height > img_width:
if scale < img_height or scale < img_width:
if img_height > img_width:
img_scale = float(scale)/float(img_height)
else:
img_scale = float(scale)/float(img_width)
@@ -115,15 +115,15 @@ while(True):
img = cv2.resize(source_img, (width, height), cv2.INTER_AREA)
mask = cv2.resize(orig_mask, (width, height), cv2.INTER_AREA)
mask_inv = cv2.resize(orig_mask_inv, (width, height), cv2.INTER_AREA)
if px == None or py == None:
continue
y1 = row-scale/2+(row-scale/2-(py-height))
y2 = row-scale/2+height+(row-scale/2-(py-height))
x1 = col-scale/2
x2 = col-scale/2+width
if y1 < 0 or y2 < 0:
continue
roi = frame[y1:y2, x1:x2]
@@ -132,15 +132,15 @@ while(True):
# join the roi_bg and roi_fg
dst = cv2.add(roi_bg, roi_fg)
frame[y1:y2, x1:x2] = dst
frame[y1:y2, x1:x2] = dst
cv2.imshow('', frame)
key = cv2.waitKey(1)
if key & 0xFF == ord('q'):
break
elif key & 0xFF == ord('w'):
show_face = not show_face
show_face = not show_face
elif key & 0xFF == ord('e'):
img_idx += 1
if img_idx > len(source_imgs)-1:

2
examples/talk_detector/talkdet.go
View File

@@ -119,7 +119,7 @@ func FindFaces(pixels []uint8) uintptr {
coords := make([]int, 0, len(dets))
go func() {
// Since in Go we cannot transfer a 2d array trough an array pointer
// Since in Go we cannot transfer a 2d array through an array pointer
// we have to transform it into 1d array.
for _, v := range dets {
coords = append(coords, v...)

2
examples/talk_detector/talkdet.py
View File

@@ -47,7 +47,7 @@ class GoPixelSlice(Structure):
("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
]
# Obtain the camera pixels and transfer them to Go trough Ctypes
# Obtain the camera pixels and transfer them to Go through Ctypes
def process_frame(pixs):
dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))

4
examples/web/README.md
View File

@@ -1,7 +1,7 @@
## Webcam demo (slow)
This demo shows how we can transfer the webcam frames from Python to Go by sending the captured frames as byte array into the standard output.
We will run the face detector over the byte arrays received from the standard output and send the result into a web browser trough a webserver.
This demo shows how we can transfer the webcam frames from Python to Go by sending the captured frames as byte array into the standard output.
We will run the face detector over the byte arrays received from the standard output and send the result into a web browser through a webserver.
### Run

6
wasm/README.md
View File

@@ -17,12 +17,12 @@ $ GOOS=js GOARCH=wasm go build -o lib.wasm wasm.go
```
### Supported keys:
<kbd>s</kbd> - Show/hide pupils<br/>
<kbd>c</kbd> - Circle trough the detection shape types (`rectangle`|`circle`|`ellipse`)<br/>
<kbd>c</kbd> - Circle through the detection shape types (`rectangle`|`circle`|`ellipse`)<br/>
<kbd>f</kbd> - Show/hide facial landmark points (hidden by default)
## Demos
For **Webassembly** related demos check this separate repo:
For **Webassembly** related demos check this separate repo:
https://github.com/esimov/pigo-wasm-demos
https://github.com/esimov/pigo-wasm-demos

2
wasm/detector/fetch.go
View File

@@ -23,7 +23,7 @@ func NewDetector() *Detector {
return &d
}
// FetchCascade retrive the cascade file trough a JS http connection.
// FetchCascade retrive the cascade file through a JS http connection.
// It should return the binary data as uint8 integers or err in case of an error.
func (d *Detector) FetchCascade(url string) ([]byte, error) {
d.respChan = make(chan []uint8)