def process_item(row):
'''Face Counting needs to be integrated here'''
try:
logger.info('Processing: <{0}> <{1}> <{2}> <{3}> <{4}>'.format(row['RASP_NAME'],
row['START_TIME'],
row['PROCESSED'],
row['S3_BUCKET'],
row['S3_KEY']))
# Download File from S3
ret_status, local_file = misc.download_from_s3(row['S3_BUCKET'], row['S3_KEY'], OUTPUT_DIR)
if ret_status:
logger.info('[{0}][{1}] Video File: {2}'.format(row['RASP_NAME'],row['START_TIME'],local_file))
#time.sleep(10)
# Run Face Count
report = fd.process(local_file)
pprint.pprint(report)
# Update Fields in DB
update_record(row, report)
#Delete the file
os.remove(local_file)
else:
logger.info('[{0}][{1}] FAILED Downloading File: {2}/{3}'.format(row['RASP_NAME'],row['START_TIME'],row['S3_BUCKET'],row['S3_KEY']))
except Exception as e:
logger.error(e)
logger.info('[{0}][{1}] FAILED Processing Video: {2}/{3}'.format(row['RASP_NAME'],row['START_TIME'],row['S3_BUCKET'],row['S3_KEY']))
#Delete the file
os.remove(local_file)
def process_item(row):
'''Face Counting needs to be integrated here'''
try:
logger.info('Processing: <{0}> <{1}> <{2}> <{3}> <{4}>'.format(
row['RASP_NAME'], row['START_TIME'], row['PROCESSED'],
row['S3_BUCKET'], row['S3_KEY']))
# Download File from S3
ret_status, local_file = misc.download_from_s3(row['S3_BUCKET'],
row['S3_KEY'],
OUTPUT_DIR)
if ret_status:
logger.info('[{0}][{1}] Video File: {2}'.format(
row['RASP_NAME'], row['START_TIME'], local_file))
#time.sleep(10)
# Run Face Count
report = fd.process(local_file)
pprint.pprint(report)
# Update Fields in DB
update_record(row, report)
#Delete the file
os.remove(local_file)
else:
logger.info('[{0}][{1}] FAILED Downloading File: {2}/{3}'.format(
row['RASP_NAME'], row['START_TIME'], row['S3_BUCKET'],
row['S3_KEY']))
except Exception as e:
logger.error(e)
logger.info('[{0}][{1}] FAILED Processing Video: {2}/{3}'.format(
row['RASP_NAME'], row['START_TIME'], row['S3_BUCKET'],
row['S3_KEY']))
#Delete the file
os.remove(local_file)
def queryDB(self):
# run through each of the cameras
for rasp in self.rasp_names:
print "processing " + rasp
ret = self.sc.query_2(RASP_NAME__eq=rasp)
# only process videos that have not been looked at AND have
# non-zero face count
for item in ret:
print "processing " + item['S3_KEY'][7:]
if ('FACE_COMPLETE' not in item or item['FACE_COMPLETE'] != 1) and item['FACE_COUNT'] > 0:
# download video to local directory
ret_status, local_file = misc.download_from_s3(item['S3_BUCKET'], item['S3_KEY'], OUTPUT_DIR)
if ret_status:
# run facial recognition
faces = self.process(local_file)
os.remove(local_file)
# if there are matches, write back to dynamo
if faces:
item['FACES'] = ','.join(faces)
item['FACE_COMPLETE'] = 1
print item['FACES'], item['FACE_COMPLETE']
item.save()
def process_item(row):
try:
logger.info('Processing: <{0}> <{1}> <{2}> <{3}> <{4}>'.format(
row['RASP_NAME'], row['START_TIME'], row['PROCESSED'],
row['S3_BUCKET'], row['S3_KEY']))
# Download File from S3
ret_status, local_file = misc.download_from_s3(row['S3_BUCKET'],
row['S3_KEY'],
OUTPUT_DIR)
if ret_status:
local_file_basename = os.path.basename(local_file)
logger.info('[{0}]'.format(local_file_basename))
local_dir = local_file + ".D"
# Create a dir
os.makedirs(local_dir)
# Dump the frames
cap = cv2.VideoCapture(local_file)
cnt = 0
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
if cnt % 5 == 0:
image_file = '{0}/frame_{1}.png'.format(local_dir, cnt)
cv2.imwrite(image_file, frame)
logger.info('[{0}] Image File Written: {1}'.format(
local_file_basename, image_file))
cnt += 1
output_file = local_dir + '/tf.class.out'
# Run Image Classification
#for f in glob.glob(local_dir + '/*'):
s = set()
for x in xrange(0, 100, 5):
f = '{0}/frame_{1}.png'.format(local_dir, x)
logger.info('[{0}] Image Classification: {1}'.format(
local_file_basename, f))
frame_id = os.path.basename(f).split(".")[0].split("_")[1]
rc = subprocess.call(['./util/tf_classify.sh', f, output_file])
with open(output_file, 'r') as f:
for l in f.readlines():
t = l.split(":")
cat = t[0].strip().split()[0]
prob = t[1].strip()
# Append as example: person(0.825)
s.add(cat)
break # Just first line (Dominant Cat)
print s
nn_categories = ",".join(s)
logger.info('[{0}] NN Dominant CATs: {1}'.format(
local_file_basename, nn_categories))
# Update Fields in DB
update_record(row, nn_categories)
#Delete the file/folder
os.remove(local_file)
shutil.rmtree(local_dir)
#print '### Sleeping for 100 secs ###'
#time.sleep(100)
else:
logger.info('[{0}][{1}] FAILED Downloading File: {2}/{3}'.format(
row['RASP_NAME'], row['START_TIME'], row['S3_BUCKET'],
row['S3_KEY']))
except Exception as e:
logger.error(e)
logger.info('[{0}][{1}] FAILED Classifying Video: {2}/{3}'.format(
row['RASP_NAME'], row['START_TIME'], row['S3_BUCKET'],
row['S3_KEY']))
#Delete the file
os.remove(local_file)
sys.exit(1)
def process_item(row):
try:
logger.info(
"Processing: <{0}> <{1}> <{2}> <{3}> <{4}>".format(
row["RASP_NAME"], row["START_TIME"], row["PROCESSED"], row["S3_BUCKET"], row["S3_KEY"]
)
)
# Download File from S3
ret_status, local_file = misc.download_from_s3(row["S3_BUCKET"], row["S3_KEY"], OUTPUT_DIR)
if ret_status:
local_file_basename = os.path.basename(local_file)
logger.info("[{0}]".format(local_file_basename))
local_dir = local_file + ".D"
# Create a dir
os.makedirs(local_dir)
# Dump the frames
cap = cv2.VideoCapture(local_file)
cnt = 0
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
if cnt % 5 == 0:
image_file = "{0}/frame_{1}.png".format(local_dir, cnt)
cv2.imwrite(image_file, frame)
logger.info("[{0}] Image File Written: {1}".format(local_file_basename, image_file))
cnt += 1
output_file = local_dir + "/tf.class.out"
# Run Image Classification
# for f in glob.glob(local_dir + '/*'):
s = set()
for x in xrange(0, 100, 5):
f = "{0}/frame_{1}.png".format(local_dir, x)
logger.info("[{0}] Image Classification: {1}".format(local_file_basename, f))
frame_id = os.path.basename(f).split(".")[0].split("_")[1]
rc = subprocess.call(["./util/tf_classify.sh", f, output_file])
with open(output_file, "r") as f:
for l in f.readlines():
t = l.split(":")
cat = t[0].strip().split()[0]
prob = t[1].strip()
# Append as example: person(0.825)
s.add(cat)
break # Just first line (Dominant Cat)
print s
nn_categories = ",".join(s)
logger.info("[{0}] NN Dominant CATs: {1}".format(local_file_basename, nn_categories))
# Update Fields in DB
update_record(row, nn_categories)
# Delete the file/folder
os.remove(local_file)
shutil.rmtree(local_dir)
# print '### Sleeping for 100 secs ###'
# time.sleep(100)
else:
logger.info(
"[{0}][{1}] FAILED Downloading File: {2}/{3}".format(
row["RASP_NAME"], row["START_TIME"], row["S3_BUCKET"], row["S3_KEY"]
)
)
except Exception as e:
logger.error(e)
logger.info(
"[{0}][{1}] FAILED Classifying Video: {2}/{3}".format(
row["RASP_NAME"], row["START_TIME"], row["S3_BUCKET"], row["S3_KEY"]
)
)
# Delete the file
os.remove(local_file)
sys.exit(1)
