def webcam_upload():
data = request.get_json()
# Preprocess the upload image
img_raw = data['data-uri'].encode()
image_path = parse_image(img_raw)
print(image_path)
(categoryPredict, positions) = detect(image_path)
print(categoryPredict)
if len(categoryPredict) > 0:
croppedDectection = []
for i in range(len(categoryPredict)):
croppedDectection.append(
'static/images/cropped-dectecion-{}.jpg'.format(i))
croppedObject = cropped.list_object(
zip(categoryPredict, croppedDectection))
else:
croppedDectection = None
objectDetection = 'static/images/object-detection.jpg'
os.remove(image_path)
return {
"crop": croppedDectection,
"full": objectDetection,
"details": positions
}
def video():
if request.method == "POST":
print(request)
_ = VideoCamera().get_frame(capture=True)
categoryPredict = detect('static/images/object-detection.jpg')
if len(categoryPredict) > 0:
croppedDectection = []
for i in range(len(categoryPredict)):
croppedDectection.append(
'images/cropped-dectecion-{}.jpg'.format(i))
croppedObject = cropped.list_object(
zip(categoryPredict, croppedDectection))
else:
croppedObject = None
return render_template('home.html',
f='../static/images/object-detection.jpg',
c=croppedObject)
return render_template('home.html', f=None, c=[])
def still():
if request.method == "POST":
f = request.files["uploadfile"]
_, ext = os.path.splitext(f.filename)
if os.path.exists(os.path.join(ptuf, "input" + ext)):
os.remove(os.path.join(ptuf, "input" + ext))
f.save(os.path.join(ptuf, "input" + ext))
categoryPredict = detect('static\images\input' + ext)
if len(categoryPredict) > 0:
croppedDectection = []
for i in range(len(categoryPredict)):
croppedDectection.append(
'images/cropped-dectecion-{}{}'.format(i, ext))
croppedObject = cropped.list_object(
zip(categoryPredict, croppedDectection))
else:
croppedObject = None
objectDetection = 'images/object-detection' + ext
return render_template('still.html',
f=objectDetection,
c=croppedObject)
df = pd.read_csv('static/product-data/Sofa bed.csv')
for category in ['Chair', 'Table', 'Lamp', 'Shelf']:
df.append(pd.read_csv('static/product-data/{}.csv'.format(category)))
randomProducts = products.random_products(df, 10)
return render_template('still.html', r=randomProducts)
def still():
if request.method == "POST":
f = request.files["uploadfile"]
_, ext = os.path.splitext(f.filename)
if os.path.exists(os.path.join(ptuf, "input" + ext)):
os.remove(os.path.join(ptuf, "input" + ext))
f.save(os.path.join(ptuf, "input" + ext))
categoryPredict = detect('static/images/input.jpg')
if len(categoryPredict) > 0:
croppedDectection = []
for i in range(len(categoryPredict)):
croppedDectection.append(
'images/cropped-dectecion-{}.jpg'.format(i))
croppedObject = cropped.list_object(
zip(categoryPredict, croppedDectection))
else:
croppedObject = None
objectDetection = 'images/object-detection.jpg'
return render_template('still.html',
f=objectDetection,
c=croppedObject)
df = pd.read_csv('static/product-data/top.csv')
for category in ['dress', 'shorts', 'skirt', 'trousers']:
df.append(pd.read_csv('static/product-data/{}.csv'.format(category)))
randomProducts = products.random_products(df, 10)
return render_template('still.html', r=randomProducts)