def main():
reqArgs = [
["o", "outputFile", "output file name"],
["i", "inputCsv", "csvfile with fire/detection data"],
['m', "mode", "mode: votepoly or camdir or pruned"],
]
optArgs = [
["s", "startRow", "starting row"],
["e", "endRow", "ending row"],
]
args = collect_args.collectArgs(reqArgs, optionalArgs=optArgs, parentParsers=[goog_helper.getParentParser()])
startRow = int(args.startRow) if args.startRow else 0
endRow = int(args.endRow) if args.endRow else 1e9
mode = args.mode
assert mode == 'votepoly' or mode == 'camdir' or mode == 'pruned'
outFile = open(args.outputFile, 'w')
dbManager = db_manager.DbManager(sqliteFile=settings.db_file,
psqlHost=settings.psqlHost, psqlDb=settings.psqlDb,
psqlUser=settings.psqlUser, psqlPasswd=settings.psqlPasswd)
lastCam = None
lastTime = None
random.seed(0)
with open(args.inputCsv) as csvFile:
csvreader = csv.reader(csvFile)
for (rowIndex, csvRow) in enumerate(csvreader):
if rowIndex < startRow:
continue
if rowIndex > endRow:
print('Reached end row', rowIndex, endRow)
break
if mode == 'votepoly':
[cameraID, timestamp, score, polygon, sourcePolygons, isRealFire] = csvRow[:6]
timestamp = int(timestamp)
logging.warning('Processing row: %d, cam: %s, ts: %s', rowIndex, cameraID, timestamp)
if cameraID == lastCam and timestamp == lastTime:
logging.warning('Duplicate row: %d, cam: %s, ts: %s', rowIndex, cameraID, timestamp)
lastCam = cameraID
lastTime = timestamp
centroid = getCentroid(polygon)
if timestamp < 1607786165: #sourcePolygons didn't exist before this
if isRealFire:
numPolys = round(getRandInterpolatedVal(settings.percentilesNumPolyFire))
else:
numPolys = round(getRandInterpolatedVal(settings.percentilesNumPolyOther))
else:
numPolys = 1
if sourcePolygons:
sourcePolygonsArr = json.loads(sourcePolygons)
numPolys = len(sourcePolygonsArr)
cameraID = patchCameraId(cameraID)
camInfo = dbManager.getCameraMapLocation(cameraID)
if camInfo == None:
logging.warning('Skipping row with camera without meta %s', cameraID)
continue
(mapImgGCS, camLatitude, camLongitude) = camInfo
else:
if mode == 'camdir':
[cameraID, isoTime, direction] = csvRow[:3]
logging.warning('Processing row: %d, cam: %s, ts: %s', rowIndex, cameraID, isoTime)
timestamp = time.mktime(dateutil.parser.parse(isoTime).timetuple())
if 'center left' in direction:
offset = -20
elif 'center right' in direction:
offset = 20
elif 'center' in direction:
offset = 0
elif 'left' in direction:
offset = -40
elif 'right' in direction:
offset = 40
else:
logging.error('Unexpected dir row: %d, dir: %s', rowIndex, direction)
continue
elif mode == 'pruned':
[_cropName, minX, _minY, maxX, _maxY, fileName] = csvRow[:6]
minX = int(minX)
maxX = int(maxX)
nameParsed = img_archive.parseFilename(fileName)
cameraID = nameParsed['cameraID']
cameraID = patchCameraId(cameraID)
timestamp = nameParsed['unixTime']
dateStr = nameParsed['isoStr'][:nameParsed['isoStr'].index('T')]
if dateStr == lastTime and cameraID == lastCam:
# logging.warning('Skip same fire. row %s', rowIndex)
continue
lastCam = cameraID
lastTime = dateStr
localFilePath = os.path.join(settings.downloadDir, fileName)
if not os.path.isfile(localFilePath):
logging.warning('Skip missing file %s, row %s', fileName, rowIndex)
continue
img = Image.open(localFilePath)
degreesInView = img_archive.getCameraFov(cameraID)
centerX = (minX + maxX) / 2
offset = centerX / img.size[0] * degreesInView - degreesInView/2
img.close()
(mapImgGCS, camLatitude, camLongitude) = dbManager.getCameraMapLocation(cameraID)
camHeading = img_archive.getHeading(cameraID)
heading = (camHeading + offset) % 360
angle = 90 - heading
distanceDegrees = 0.2 # approx 14 miles
fireLat = camLatitude + math.sin(angle*math.pi/180)*distanceDegrees
fireLong = camLongitude + math.cos(angle*math.pi/180)*distanceDegrees
centroid = (fireLat, fireLong)
score = getRandInterpolatedVal(settings.percentilesScoreFire)
numPolys = round(getRandInterpolatedVal(settings.percentilesNumPolyFire))
isRealFire = 1
logging.warning('Processing row: %d, heading: %s, centroid: %s, score: %s, numpoly: %s', rowIndex, heading, centroid, score, numPolys)
if not keepData(score, centroid, numPolys, isRealFire):
logging.warning('Skipping Mexico fire row %d, camera %s', rowIndex, cameraID)
continue
(weatherCentroid, weatherCamera) = weather.getWeatherData(dbManager, cameraID, timestamp, centroid, (camLatitude, camLongitude))
if not weatherCentroid:
logging.warning('Skipping row %d', rowIndex)
continue
# logging.warning('Weather %s', weatherCentroid)
outputWithWeather(outFile, score, timestamp, centroid, numPolys, weatherCentroid, weatherCamera, isRealFire)
logging.warning('Processed row: %d, cam: %s, ts: %s', rowIndex, cameraID, timestamp)
outFile.close()
def main():
reqArgs = [
["o", "outputDir", "local directory to save images segments"],
["i", "inputCsv", "csvfile with contents of Cropped Images"],
]
optArgs = [
["s", "startRow", "starting row"],
["e", "endRow", "ending row"],
["d", "display", "(optional) specify any value to display image and boxes"],
["x", "minDiffX", "(optional) override default minDiffX of 299"],
["y", "minDiffY", "(optional) override default minDiffY of 299"],
["a", "minArea", "(optional) override default throw away areas < 1/100 of 299x299"],
["t", "throwSize", "(optional) override default throw away size of 598x598"],
["g", "growRatio", "(optional) override default grow ratio of 1.2"],
["m", "minusMinutes", "(optional) subtract images from given number of minutes ago"],
["r", "review", "(optional) download original crops without augmentation"],
]
args = collect_args.collectArgs(reqArgs, optionalArgs=optArgs, parentParsers=[goog_helper.getParentParser()])
startRow = int(args.startRow) if args.startRow else 0
endRow = int(args.endRow) if args.endRow else 1e9
minDiffX = int(args.minDiffX) if args.minDiffX else 299
minDiffY = int(args.minDiffY) if args.minDiffY else 299
throwSize = int(args.throwSize) if args.throwSize else 299*2
growRatio = float(args.growRatio) if args.growRatio else 1.2
minArea = int(args.minArea) if args.minArea else int(299*2.99)
minusMinutes = int(args.minusMinutes) if args.minusMinutes else 0
googleServices = goog_helper.getGoogleServices(settings, args)
camArchives = img_archive.getHpwrenCameraArchives(settings.hpwrenArchives)
if minusMinutes:
timeGapDelta = datetime.timedelta(seconds = 60*minusMinutes)
cameraCache = {}
skippedTiny = []
skippedHuge = []
skippedArchive = []
with open(args.inputCsv) as csvFile:
csvreader = csv.reader(csvFile)
for (rowIndex, csvRow) in enumerate(csvreader):
if rowIndex < startRow:
continue
if rowIndex > endRow:
print('Reached end row', rowIndex, endRow)
break
[cropName, minX, minY, maxX, maxY, fileName] = csvRow[:6]
minX = int(minX)
minY = int(minY)
maxX = int(maxX)
maxY = int(maxY)
oldCoords = (minX, minY, maxX, maxY)
if ((maxX - minX) > throwSize) or ((maxY - minY) > throwSize):
logging.warning('Skip large image: dx=%d, dy=%d, name=%s', maxX - minX, maxY - minY, fileName)
skippedHuge.append((rowIndex, fileName, maxX - minX, maxY - minY))
continue
if ((maxX - minX) * (maxY - minY)) < minArea:
logging.warning('Skipping tiny image with area: %d, name=%s', (maxX - minX) * (maxY - minY), fileName)
skippedTiny.append((rowIndex, fileName, (maxX - minX) * (maxY - minY)))
continue
nameParsed = img_archive.parseFilename(fileName)
imgDT = datetime.datetime.fromtimestamp(nameParsed['unixTime'])
localFilePath = os.path.join(settings.downloadDir, fileName)
if not os.path.isfile(localFilePath):# if file has not been downloaded by a previous iteration
files = img_archive.getHpwrenImages(googleServices, settings, settings.downloadDir, camArchives, nameParsed['cameraID'], imgDT, imgDT, 1)
localFilePath = files[0]
imgOrig = Image.open(localFilePath)
# if in subracted images mode, download an earlier image and subtract
if minusMinutes:
dt = imgDT - timeGapDelta
nameParsed['unixTime'] -= 60*minusMinutes
earlierName = img_archive.repackFileName(nameParsed)
earlierImgPath = os.path.join(settings.downloadDir, earlierName)
if not os.path.isfile(earlierImgPath):# if file has not been downloaded by a previous iteration
files = img_archive.getHpwrenImages(googleServices, settings, settings.downloadDir, camArchives, nameParsed['cameraID'], dt, dt, 1)
if files:
earlierImgPath = files[0]
else:
logging.warning('Skipping image without prior image: %s, %s', str(dt), fileName)
skippedArchive.append((rowIndex, fileName, dt))
continue
logging.warning('Subtracting old image %s', earlierImgPath)
earlierImg = Image.open(earlierImgPath)
diffImg = img_archive.diffImages(imgOrig, earlierImg)
extremas = diffImg.getextrema()
if extremas[0][0] == 128 or extremas[0][1] == 128 or extremas[1][0] == 128 or extremas[1][1] == 128 or extremas[2][0] == 128 or extremas[2][1] == 128:
logging.warning('Skipping no diffs %s, name=%s', str(extremas), fileName)
skippedTiny.append((rowIndex, fileName, extremas))
continue
# realImgOrig = imgOrig # is this useful?
imgOrig = diffImg
fileNameParts = os.path.splitext(fileName)
fileName = str(fileNameParts[0]) + ('_Diff%d' % minusMinutes) + fileNameParts[1]
if args.review:
cropCoords = [oldCoords]
else:
# crop the full sized image to show just the smoke, but shifted and flipped
# shifts and flips increase number of segments for training and also prevent overfitting by perturbing data
cropCoords = getCropCoords((minX, minY, maxX, maxY), minDiffX, minDiffY, growRatio, (imgOrig.size[0], imgOrig.size[1]))
for newCoords in cropCoords:
# XXXX - save work if old=new?
logging.warning('coords old %s, new %s', str(oldCoords), str(newCoords))
imgNameNoExt = str(os.path.splitext(fileName)[0])
cropImgName = imgNameNoExt + '_Crop_' + 'x'.join(list(map(lambda x: str(x), newCoords))) + '.jpg'
cropImgPath = os.path.join(args.outputDir, cropImgName)
cropped_img = imgOrig.crop(newCoords)
cropped_img.save(cropImgPath, format='JPEG')
if not args.review:
flipped_img = cropped_img.transpose(Image.FLIP_LEFT_RIGHT)
flipImgName = imgNameNoExt + '_Crop_' + 'x'.join(list(map(lambda x: str(x), newCoords))) + '_Flip.jpg'
flipImgPath = os.path.join(args.outputDir, flipImgName)
flipped_img.save(flipImgPath, format='JPEG')
logging.warning('Processed row: %d, file: %s', rowIndex, fileName)
if args.display:
displayCoords = [oldCoords] + cropCoords
displayImageWithScores(imgOrig, displayCoords)
imageDisplay(imgOrig)
logging.warning('Skipped tiny images %d, %s', len(skippedTiny), str(skippedTiny))
logging.warning('Skipped huge images %d, %s', len(skippedHuge), str(skippedHuge))
logging.warning('Skipped images without archives %d, %s', len(skippedArchive), str(skippedArchive))
def main():
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # quiet down tensorflow logging
reqArgs = [
["d", "directory", "directory containing the image sets"],
["o", "outputFile", "output file name"],
]
optArgs = [
["l", "labels", "labels file generated during retraining"],
["m", "model", "model file generated during retraining"],
]
args = collect_args.collectArgs(reqArgs, optionalArgs=optArgs)
model_file = args.model if args.model else settings.model_file
labels_file = args.labels if args.labels else settings.labels_file
DetectionPolicyClass = policies.get_policies()[settings.detectionPolicy]
detectionPolicy = DetectionPolicyClass(args,
None,
0,
stateless=True,
modelLocation=model_file)
test_data = []
image_name = []
crop_name = []
score_name = []
class_name = []
image_name += ["Image"]
crop_name += ["Crop"]
score_name += ["Score"]
class_name += ["Class"]
smokeDir = os.path.join(args.directory, 'test_set_smoke')
smoke_image_list = listJpegs(smokeDir)
logging.warning('Found %d images of smoke', len(smoke_image_list))
nonSmokeDir = os.path.join(args.directory, 'test_set_other')
other_image_list = listJpegs(nonSmokeDir)
logging.warning('Found %d images of nonSmoke', len(other_image_list))
smokeFile = os.path.join(args.directory, 'test_smoke.txt')
np.savetxt(smokeFile, smoke_image_list, fmt="%s")
nonSmokeFile = os.path.join(args.directory, 'test_other.txt')
np.savetxt(nonSmokeFile, other_image_list, fmt="%s")
outFile = open(args.outputFile, 'w')
(i, cr, s, cl, positives,
negatives) = classifyImages(detectionPolicy, smoke_image_list, 'smoke',
args.outputFile)
image_name += i
crop_name += cr
score_name += s
class_name += cl
logging.warning('Done with smoke images')
truePositive = len(positives)
falseNegative = len(smoke_image_list) - len(positives)
logging.warning('True Positive: %d', truePositive)
logging.warning('False Negative: %d', falseNegative)
outFile.write('True Positives: ' + ', '.join(positives) + '\n')
outFile.write('False Negative: ' + ', '.join(negatives) + '\n')
(i, cr, s, cl, positives,
negatives) = classifyImages(detectionPolicy, other_image_list, 'other',
args.outputFile)
image_name += i
crop_name += cr
score_name += s
class_name += cl
logging.warning('Done with nonSmoke images')
falsePositive = len(positives)
trueNegative = len(other_image_list) - len(positives)
logging.warning('False Positive: %d', falsePositive)
logging.warning('True Negative: %d', trueNegative)
outFile.write('False Positives: ' + ', '.join(positives) + '\n')
outFile.write('True Negative: ' + ', '.join(negatives) + '\n')
accuracy = safeDiv(
truePositive + trueNegative,
truePositive + trueNegative + falsePositive + falseNegative)
logging.warning('Accuracy: %f', accuracy)
precision = safeDiv(truePositive, truePositive + falsePositive)
logging.warning('Precision: %f', precision)
recall = safeDiv(truePositive, truePositive + falseNegative)
logging.warning('Recall: %f', recall)
f1 = safeDiv(2 * precision * recall, precision + recall)
logging.warning('F1: %f', f1)
test_data = [image_name, crop_name, score_name, class_name]
np.savetxt(outFile, np.transpose(test_data), fmt="%s")
outFile.close()
print("DONE")
def main():
reqArgs = [
["i", "inputDir", "directory containing TFRecord files"],
[
"o", "outputDir",
"directory to write out checkpoints and tensorboard logs"
],
["a", "algorithm", "adam, nadam, or rmsprop"],
]
optArgs = [
[
"m", "maxEpochs", "(optional) max number of epochs (default 1000)",
int
],
["r", "resumeModel", "resume training from given saved model"],
["s", "startEpoch", "epoch to resume from (epoch from resumeModel)"],
["t", "stepsPerEpoch", "(optional) number of steps per epoch", int],
[
"v", "valStepsPerEpoch",
"(optional) number of validation steps per epoch", int
],
]
args = collect_args.collectArgs(
reqArgs,
optionalArgs=optArgs,
parentParsers=[goog_helper.getParentParser()])
batch_size = 64
max_epochs = args.maxEpochs if args.maxEpochs else 1000
steps_per_epoch = args.stepsPerEpoch if args.stepsPerEpoch else 2000
overshoot_epochs = 30 #number of epochs over which validation loss hasnt decreased to stop training at
val_steps = args.valStepsPerEpoch if args.valStepsPerEpoch else 200
#val_steps only needed for now because of a bug in tf2.0, which should be fixed in next version
#TODO: either set this to # of validation examples /batch size (i.e. figure out num validation examples)
#or upgrade to TF2.1 when its ready and automatically go thorugh the whole set
train_filenames = glob.glob(
os.path.join(args.inputDir, 'firecam_train_*.tfrecord'))
val_filenames = glob.glob(
os.path.join(args.inputDir, 'firecam_validation_*.tfrecord'))
logging.warning('Found %d training files, and %d validation files',
len(train_filenames), len(val_filenames))
if (len(train_filenames) == 0) or (len(val_filenames) == 0):
logging.error('Could not find data in %s', args.inputDir)
exit(1)
raw_dataset_train = tf.data.TFRecordDataset(train_filenames)
raw_dataset_val = tf.data.TFRecordDataset(val_filenames)
dataset_train = raw_dataset_train.map(_parse_function).repeat(
max_epochs * steps_per_epoch).shuffle(batch_size * 5).batch(batch_size)
dataset_val = raw_dataset_val.map(_parse_function).repeat().batch(
batch_size)
if args.resumeModel:
inception = tf_helper.loadModel(args.resumeModel)
assert int(args.startEpoch) > 0
initial_epoch = int(args.startEpoch)
else:
inception = keras.applications.inception_v3.InceptionV3(
weights=None, include_top=True, input_tensor=None, classes=2)
initial_epoch = 0
if args.algorithm == "adam":
# optimizer = tf.keras.optimizers.Adam(learning_rate=0.001, beta_1=0.9, beta_2=0.999, amsgrad=False)
optimizer = tf.keras.optimizers.Adam(decay=1e-06, amsgrad=True)
elif args.algorithm == "nadam":
optimizer = tf.keras.optimizers.Nadam()
elif args.algorithm == "rmsprop":
optimizer = tf.keras.optimizers.RMSprop(decay=1e-06)
else:
logging.error('Unsupported algo %s', args.algorithm)
exit(1)
inception.compile(optimizer=optimizer,
loss=tf.keras.losses.BinaryCrossentropy(),
metrics=['accuracy'])
logdir = os.path.join(args.outputDir,
datetime.datetime.now().strftime("%Y%m%d-%H%M%S"))
callbacks = [
keras.callbacks.EarlyStopping(monitor='val_loss',
patience=overshoot_epochs),
keras.callbacks.ModelCheckpoint(filepath=os.path.join(
args.outputDir, 'model_{epoch}'),
monitor='val_loss',
save_best_only=True),
LRTensorBoard(log_dir=logdir)
]
logging.warning('Start training')
inception.fit(dataset_train,
validation_data=dataset_val,
epochs=max_epochs,
initial_epoch=initial_epoch,
steps_per_epoch=steps_per_epoch,
validation_steps=val_steps,
callbacks=callbacks)
logging.warning('Done training')
def main():
reqArgs = [
["o", "outputDir", "local directory to save images segments"],
["i", "inputCsv", "csvfile with contents of Cropped Images"],
]
optArgs = [
["s", "startRow", "starting row"],
["e", "endRow", "ending row"],
["x", "minSizeX", "(optional) override default minSizeX of 299"],
["y", "minSizeY", "(optional) override default minSizeY of 299"],
["a", "minArea", "(optional) override default 0 for minimum area"],
["t", "throwSize", "(optional) override default throw away size of 598x598"],
["g", "growRatio", "(optional) override default grow ratio of 1.2"],
["m", "minusMinutes", "(optional) subtract images from given number of minutes ago"],
["r", "recropType", "recrop type: 'raw', 'center', 'full', 'shift', 'augment' (default)"],
]
args = collect_args.collectArgs(reqArgs, optionalArgs=optArgs, parentParsers=[goog_helper.getParentParser()])
startRow = int(args.startRow) if args.startRow else 0
endRow = int(args.endRow) if args.endRow else 1e9
minSizeX = int(args.minSizeX) if args.minSizeX else 299
minSizeY = int(args.minSizeY) if args.minSizeY else 299
throwSize = int(args.throwSize) if args.throwSize else 299*2
growRatio = float(args.growRatio) if args.growRatio else 1.2
minArea = int(args.minArea) if args.minArea else 0
minusMinutes = int(args.minusMinutes) if args.minusMinutes else 0
recropType = args.recropType if args.recropType else 'augment'
random.seed(0)
googleServices = goog_helper.getGoogleServices(settings, args)
camArchives = img_archive.getHpwrenCameraArchives(settings.hpwrenArchives)
downloadDirCache = img_archive.cacheDir(settings.downloadDir, settings.downloadDir)
if minusMinutes:
timeGapDelta = datetime.timedelta(seconds = 60*minusMinutes)
cameraCache = {}
skippedTiny = []
skippedHuge = []
skippedArchive = []
with open(args.inputCsv) as csvFile:
csvreader = csv.reader(csvFile)
for (rowIndex, csvRow) in enumerate(csvreader):
if rowIndex < startRow:
continue
if rowIndex > endRow:
print('Reached end row', rowIndex, endRow)
break
[_unused_cropName, minX, minY, maxX, maxY, fileName] = csvRow[:6]
minX = int(minX)
minY = int(minY)
maxX = int(maxX)
maxY = int(maxY)
oldCoords = (minX, minY, maxX, maxY)
if ((maxX - minX) > throwSize) or ((maxY - minY) > throwSize):
logging.warning('Skip large image: dx=%d, dy=%d, name=%s', maxX - minX, maxY - minY, fileName)
skippedHuge.append((rowIndex, fileName, maxX - minX, maxY - minY))
continue
if ((maxX - minX) * (maxY - minY)) < minArea:
logging.warning('Skipping tiny image with area: %d, name=%s', (maxX - minX) * (maxY - minY), fileName)
skippedTiny.append((rowIndex, fileName, (maxX - minX) * (maxY - minY)))
continue
nameParsed = img_archive.parseFilename(fileName)
imgDT = datetime.datetime.fromtimestamp(nameParsed['unixTime'])
(imgOrig, imgFilePath) = getArchiveImage(googleServices, downloadDirCache, camArchives, nameParsed['cameraID'], fileName, imgDT)
if not imgOrig:
logging.warning('Skip image without archive: %s', fileName)
skippedArchive.append((rowIndex, fileName, imgDT))
continue
# find coordinates for cropping
if recropType == 'raw':
cropCoords = [oldCoords]
elif recropType == 'full': # useful for generating full diffs
cropCoords = [(0, 0, imgOrig.size[0], imgOrig.size[1])]
else:
# crop the full sized image to show just the smoke, but shifted and flipped
# shifts and flips increase number of segments for training and also prevent overfitting by perturbing data
cropCoords = getCropCoords((minX, minY, maxX, maxY), minSizeX, minSizeY, growRatio, (imgOrig.size[0], imgOrig.size[1]), recropType)
fullImage = False
if len(cropCoords) == 1 and cropCoords[0][0] == 0 and cropCoords[0][1] == 0 and cropCoords[0][2] == imgOrig.size[0] and cropCoords[0][3] == imgOrig.size[1]:
fullImage = True
assert fullImage or ('minX' not in nameParsed) # disallow crops of crops
# find extrema (min/max) crop coordinates to crop the original image to speed up processing
extremaCoords = list(cropCoords[0])
for coords in cropCoords:
extremaCoords[0] = min(extremaCoords[0], coords[0])
extremaCoords[1] = min(extremaCoords[1], coords[1])
extremaCoords[2] = max(extremaCoords[2], coords[2])
extremaCoords[3] = max(extremaCoords[3], coords[3])
imgOrig = imgOrig.crop(extremaCoords)
# if in subracted images mode, download an earlier image and subtract
if minusMinutes:
if not img_archive.findCameraInArchive(camArchives, nameParsed['cameraID']):
earlierImg = None
files = img_archive.cacheFetchRange(downloadDirCache, nameParsed['cameraID'], nameParsed['unixTime'], -minusMinutes*60, -10*minusMinutes*60)
if files:
earlierImg = findAlignedImage(imgFilePath, files, fullImage)
if not files or not earlierImg:
logging.warning('Skipping image without prior image: %s', fileName)
skippedArchive.append((rowIndex, fileName, None))
continue
else:
nameParsed['unixTime'] -= 60*minusMinutes
earlierName = img_archive.repackFileName(nameParsed)
dt = imgDT - timeGapDelta
(earlierImg, _) = getArchiveImage(googleServices, downloadDirCache, camArchives, nameParsed['cameraID'], earlierName, dt)
if not earlierImg:
logging.warning('Skipping image without prior image: %s, %s', str(dt), fileName)
skippedArchive.append((rowIndex, fileName, dt))
continue
logging.warning('Subtracting old image %s', earlierName)
earlierImg = earlierImg.crop(extremaCoords)
diffImg = img_archive.diffWithChecks(imgOrig, earlierImg)
if not diffImg:
skippedTiny.append((rowIndex, fileName))
continue
imgOrig = diffImg
fileNameParts = os.path.splitext(fileName)
fileName = str(fileNameParts[0]) + ('_Diff%d' % minusMinutes) + fileNameParts[1]
for newCoords in cropCoords:
logging.warning('coords old %s, new %s', str(oldCoords), str(newCoords))
parsed = img_archive.parseFilename(fileName)
if not fullImage:
parsed['minX'] = newCoords[0]
parsed['minY'] = newCoords[1]
parsed['maxX'] = newCoords[2]
parsed['maxY'] = newCoords[3]
if minusMinutes:
parsed['diffMinutes'] = 1
cropImgName = img_archive.repackFileName(parsed)
cropImgPath = os.path.join(args.outputDir, cropImgName)
cropped_img = imgOrig.crop((newCoords[0] - extremaCoords[0], newCoords[1] - extremaCoords[1],
newCoords[2] - extremaCoords[0], newCoords[3] - extremaCoords[1]))
cropped_img.save(cropImgPath, format='JPEG', quality=95)
if recropType == 'augment':
flipped_img = cropped_img.transpose(Image.FLIP_LEFT_RIGHT)
flipImgName = cropImgName.replace('.jpg', '_Flip.jpg')
flipImgPath = os.path.join(args.outputDir, flipImgName)
flipped_img.save(flipImgPath, format='JPEG', quality=95)
logging.warning('Processed row: %d, file: %s', rowIndex, fileName)
logging.warning('Skipped tiny images %d, %s', len(skippedTiny), str(skippedTiny))
logging.warning('Skipped huge images %d, %s', len(skippedHuge), str(skippedHuge))
logging.warning('Skipped images without archives %d, %s', len(skippedArchive), str(skippedArchive))
def main():
reqArgs = [
["o", "operation", "add (includes update), delete, list"],
]
optArgs = [
["n", "name", "name (ID) of user"],
["m", "email", "email address of user"],
["p", "phone", "phone number of user"],
["s", "startTime", "starting date and time in ISO format (e.g., 2019-02-22T14:34:56 in Pacific time zone)"],
["e", "endTime", "ending date and time in ISO format (e.g., 2019-02-22T14:34:56 in Pacific time zone)"],
]
args = collect_args.collectArgs(reqArgs, optionalArgs=optArgs)
startTime = parseTimeStr(args.startTime) if args.startTime else None
endTime = parseTimeStr(args.endTime) if args.endTime else None
dbManager = db_manager.DbManager(sqliteFile=settings.db_file,
psqlHost=settings.psqlHost, psqlDb=settings.psqlDb,
psqlUser=settings.psqlUser, psqlPasswd=settings.psqlPasswd)
notifications = dbManager.getNotifications()
activeEmails = dbManager.getNotifications(filterActiveEmail=True)
activePhones = dbManager.getNotifications(filterActivePhone=True)
logging.warning('Num all notifications: %d. Active emails: %d. Active phones: %d',
len(notifications), len(activeEmails), len(activePhones))
if args.operation == 'list':
for n in notifications:
printNoficiation(n)
return
assert args.name
matching = list(filter(lambda x: x['name'] == args.name, notifications))
logging.warning('Found %d matching for name %s', len(matching), args.name)
if matching:
printNoficiation(matching[0])
if args.operation == 'add':
assert startTime and endTime
assert endTime >= startTime
assert args.email or args.phone
if not matching:
# insert new entry
dbRow = {
'name': args.name,
}
if args.email:
dbRow['email'] = args.email
dbRow['EmailStartTime'] = startTime
dbRow['EmailEndTime'] = endTime
if args.phone:
dbRow['phone'] = args.phone
dbRow['PhoneStartTime'] = startTime
dbRow['PhoneEndTime'] = endTime
dbManager.add_data('notifications', dbRow)
logging.warning('Successfully added notification for %s', args.name)
else:
# update existing entry
if args.email:
sqlTemplate = """UPDATE notifications SET email='%s',EmailStartTime=%s,EmailEndTime=%s WHERE name = '%s' """
sqlStr = sqlTemplate % (args.email, startTime, endTime, args.name)
dbManager.execute(sqlStr)
if args.phone:
sqlTemplate = """UPDATE notifications SET phone='%s',PhoneStartTime=%s,PhoneEndTime=%s WHERE name = '%s' """
sqlStr = sqlTemplate % (args.phone, startTime, endTime, args.name)
dbManager.execute(sqlStr)
logging.warning('Successfully updated notification for %s', args.name)
notifications = dbManager.getNotifications()
matching = list(filter(lambda x: x['name'] == args.name, notifications))
printNoficiation(matching[0])
elif args.operation == 'delete':
sqlTemplate = """DELETE FROM notifications WHERE name = '%s' """
sqlStr = sqlTemplate % (args.name)
dbManager.execute(sqlStr)
else:
logging.error('Unexpected operation: %s', args.operation)
def main():
reqArgs = [
["m", "mode", "add, delete, enable, disable, stats, or list"],
]
optArgs = [
["c", "cameraID", "ID of the camera (e.g., mg-n-mobo-c)"],
["u", "url", "url to get images from camera"],
]
args = collect_args.collectArgs(reqArgs, optionalArgs=optArgs)
dbManager = db_manager.DbManager(sqliteFile=settings.db_file,
psqlHost=settings.psqlHost, psqlDb=settings.psqlDb,
psqlUser=settings.psqlUser, psqlPasswd=settings.psqlPasswd)
cameraInfos = dbManager.get_sources(activeOnly=False)
logging.warning('Num all cameras: %d', len(cameraInfos))
logging.warning('Num active cameras: %d', len(list(filter(lambda x: x['dormant'] == 0, cameraInfos))))
if args.mode == 'list':
logging.warning('All cameras: %s', list(map(lambda x: x['name'], cameraInfos)))
return
matchingCams = list(filter(lambda x: x['name'] == args.cameraID, cameraInfos))
logging.warning('Found %d matching cams for ID %s', len(matchingCams), args.cameraID)
if args.mode == 'add':
if len(matchingCams) != 0:
logging.error('Camera with ID %s already exists: %s', args.cameraID, matchingCams)
exit(1)
dbRow = {
'name': args.cameraID,
'url': args.url,
'dormant': 0,
'randomID': random.random(),
'last_date': datetime.datetime.now().isoformat()
}
dbManager.add_data('sources', dbRow)
logging.warning('Successfully added camera %s', args.cameraID)
return
if len(matchingCams) != 1:
logging.error('Cannot find camera with ID %s: %s', args.cameraID, matchingCams)
exit(1)
camInfo = matchingCams[0]
logging.warning('Cam details: %s', camInfo)
if args.mode == 'delete':
sqlTemplate = """DELETE FROM sources WHERE name = '%s' """
execCameraSql(dbManager, sqlTemplate, args.cameraID, isQuery=False)
return
if args.mode == 'enable':
if camInfo['dormant'] == 0:
logging.error('Camera already enabled: dormant=%d', camInfo['dormant'])
exit(1)
sqlTemplate = """UPDATE sources SET dormant=0 WHERE name = '%s' """
execCameraSql(dbManager, sqlTemplate, args.cameraID, isQuery=False)
return
if args.mode == 'disable':
if camInfo['dormant'] == 1:
logging.error('Camera already disabled: dormant=%d', camInfo['dormant'])
exit(1)
sqlTemplate = """UPDATE sources SET dormant=1 WHERE name = '%s' """
execCameraSql(dbManager, sqlTemplate, args.cameraID, isQuery=False)
return
if args.mode == 'stats':
sqlTemplate = """SELECT max(timestamp) as maxtime FROM scores WHERE CameraName = '%s' """
dbResult = execCameraSql(dbManager, sqlTemplate, args.cameraID, isQuery=True)
logging.warning('Most recent image scanned: %s', getTime(dbResult))
sqlTemplate = """SELECT max(timestamp) as maxtime FROM detections WHERE CameraName = '%s' """
dbResult = execCameraSql(dbManager, sqlTemplate, args.cameraID, isQuery=True)
logging.warning('Most recent smoke detection: %s', getTime(dbResult))
sqlTemplate = """SELECT max(timestamp) as maxtime FROM alerts WHERE CameraName = '%s' """
dbResult = execCameraSql(dbManager, sqlTemplate, args.cameraID, isQuery=True)
logging.warning('Most recent smoke alert: %s', getTime(dbResult))
return
logging.error('Unexpected mode: %s', args.mode)
exit(1)
def main():
optArgs = [
["b", "heartbeat", "filename used for heartbeating check"],
["c", "collectPositves", "collect positive segments for training data"],
["t", "time", "Time breakdown for processing images"],
["m", "minusMinutes", "(optional) subtract images from given number of minutes ago"],
["r", "restrictType", "Only process images from cameras of given type"],
["s", "startTime", "(optional) performs search with modifiedTime > startTime"],
["e", "endTime", "(optional) performs search with modifiedTime < endTime"],
]
args = collect_args.collectArgs([], optionalArgs=optArgs, parentParsers=[goog_helper.getParentParser()])
minusMinutes = int(args.minusMinutes) if args.minusMinutes else 0
# TODO: Fix googleServices auth to resurrect email alerts
# googleServices = goog_helper.getGoogleServices(settings, args)
googleServices = None
dbManager = db_manager.DbManager(sqliteFile=settings.db_file,
psqlHost=settings.psqlHost, psqlDb=settings.psqlDb,
psqlUser=settings.psqlUser, psqlPasswd=settings.psqlPasswd)
cameras = dbManager.get_sources(activeOnly=True, restrictType=args.restrictType)
startTimeDT = dateutil.parser.parse(args.startTime) if args.startTime else None
endTimeDT = dateutil.parser.parse(args.endTime) if args.endTime else None
timeRangeSeconds = None
useArchivedImages = False
camArchives = img_archive.getHpwrenCameraArchives(settings.hpwrenArchives)
DetectionPolicyClass = policies.get_policies()[settings.detectionPolicy]
detectionPolicy = DetectionPolicyClass(args, dbManager, minusMinutes, stateless=useArchivedImages)
constants = { # dictionary of constants to reduce parameters in various functions
'args': args,
'googleServices': googleServices,
'camArchives': camArchives,
'dbManager': dbManager,
}
if startTimeDT or endTimeDT:
assert startTimeDT and endTimeDT
timeRangeSeconds = (endTimeDT-startTimeDT).total_seconds()
assert timeRangeSeconds > 0
assert args.collectPositves
useArchivedImages = True
random.seed(0) # fixed seed guarantees same randomized ordering. Should make this optional argument in future
processingTimeTracker = initializeTimeTracker()
while True:
classifyImgPath = None
timeStart = time.time()
if useArchivedImages:
(cameraID, timestamp, imgPath, classifyImgPath) = \
getArchivedImages(constants, cameras, startTimeDT, timeRangeSeconds, minusMinutes)
# elif minusMinutes: to be resurrected using archive functionality
else: # regular (non diff mode), grab image and process
(cameraID, timestamp, imgPath, md5) = getNextImage(dbManager, cameras)
classifyImgPath = imgPath
if not cameraID:
continue # skip to next camera
timeFetch = time.time()
image_spec = [{}]
image_spec[-1]['path'] = classifyImgPath
image_spec[-1]['timestamp'] = timestamp
image_spec[-1]['cameraID'] = cameraID
detectionResult = detectionPolicy.detect(image_spec)
timeDetect = time.time()
if detectionResult['fireSegment']:
if not isDuplicateAlert(dbManager, cameraID, timestamp):
alertFire(constants, cameraID, timestamp, imgPath, detectionResult['fireSegment'])
deleteImageFiles(imgPath, imgPath)
if (args.heartbeat):
heartBeat(args.heartbeat)
timePost = time.time()
updateTimeTracker(processingTimeTracker, timePost - timeStart)
if args.time:
if not detectionResult['timeMid']:
detectionResult['timeMid'] = timeDetect
logging.warning('Timings: fetch=%.2f, detect0=%.2f, detect1=%.2f post=%.2f',
timeFetch-timeStart, detectionResult['timeMid']-timeFetch, timeDetect-detectionResult['timeMid'], timePost-timeDetect)
# free all memory for current iteration and trigger GC to prevent memory growth
detectionResult = None
gc.collect()
def main():
reqArgs = [
["o", "outputDir", "local directory to save diff image segments"],
[
"i", "inputDir",
"input local directory containing nonSmoke image segments"
],
[
"m", "minusMinutes",
"subtract images from given number of minutes ago"
],
]
optArgs = [
["s", "startRow", "starting row"],
["e", "endRow", "ending row"],
["f", "fullImages", "(optional) process full images vs cropped"],
]
args = collect_args.collectArgs(
reqArgs,
optionalArgs=optArgs,
parentParsers=[goog_helper.getParentParser()])
minusMinutes = int(args.minusMinutes)
startRow = int(args.startRow) if args.startRow else 0
endRow = int(args.endRow) if args.endRow else 1e9
fullImages = True if args.fullImages else False
googleServices = goog_helper.getGoogleServices(settings, args)
camArchives = img_archive.getHpwrenCameraArchives(settings.hpwrenArchives)
timeGapDelta = datetime.timedelta(seconds=60 * minusMinutes)
skippedBadParse = []
skippedArchive = []
imageFileNames = sorted(os.listdir(args.inputDir))
rowIndex = -1
for fileName in imageFileNames:
rowIndex += 1
if rowIndex < startRow:
continue
if rowIndex > endRow:
print('Reached end row', rowIndex, endRow)
break
if (fileName[:3] == 'v2_') or (fileName[:3]
== 'v3_') or (not 'mobo-c' in fileName):
continue # skip replicated files
logging.warning('Processing row %d, file: %s', rowIndex, fileName)
parsedName = img_archive.parseFilename(fileName)
if (not parsedName) or parsedName['diffMinutes'] or (
('minX' not in parsedName) and not fullImages):
logging.warning(
'Skipping file with unexpected parsed data: %s, %s', fileName,
str(parsedName))
skippedBadParse.append((rowIndex, fileName, parsedName))
continue # skip files without crop info or with diff
parsedName['unixTime'] -= 60 * minusMinutes
earlierName = img_archive.repackFileName(parsedName)
earlierImgPath = os.path.join(settings.downloadDir, earlierName)
if not os.path.isfile(
earlierImgPath
): # if file has not been downloaded by a previous iteration
dt = datetime.datetime.fromtimestamp(parsedName['unixTime'])
dt -= timeGapDelta
files = img_archive.getHpwrenImages(googleServices, settings,
settings.downloadDir,
camArchives,
parsedName['cameraID'], dt, dt,
1)
if files:
earlierImgPath = files[0]
else:
logging.warning('Skipping image without prior image: %s, %s',
str(dt), fileName)
skippedArchive.append((rowIndex, fileName, dt))
continue
logging.warning('Subtracting old image %s', earlierImgPath)
imgOrig = Image.open(os.path.join(args.inputDir, fileName))
earlierImg = Image.open(earlierImgPath)
if fullImages:
diffImg = img_archive.diffSmoothImages(imgOrig, earlierImg)
else:
croppedEarlyImg = earlierImg.crop(
(parsedName['minX'], parsedName['minY'], parsedName['maxX'],
parsedName['maxY']))
diffImg = img_archive.diffImages(imgOrig, croppedEarlyImg)
extremas = diffImg.getextrema()
if extremas[0][0] == 128 or extremas[0][1] == 128 or extremas[1][
0] == 128 or extremas[1][1] == 128 or extremas[2][
0] == 128 or extremas[2][1] == 128:
logging.warning('Skipping no diffs %s, name=%s', str(extremas),
fileName)
skippedBadParse.append((rowIndex, fileName, extremas))
continue
parsedName['diffMinutes'] = minusMinutes
diffImgPath = os.path.join(args.outputDir,
img_archive.repackFileName(parsedName))
logging.warning('Saving new image %s', diffImgPath)
diffImg.save(diffImgPath, format='JPEG', quality=95)
logging.warning('Skipped bad parse %d, %s', len(skippedBadParse),
str(skippedBadParse))
logging.warning('Skipped images without archives %d, %s',
len(skippedArchive), str(skippedArchive))
def main():
reqArgs = [
[
"s", "startTime",
"starting date and time in ISO format (e.g., 2019-02-22T14:34:56 in Pacific time zone)"
],
]
optArgs = [
["c", "cameraID", "ID (code name) of camera"],
['n', 'longitude', 'longitude of fire', float],
['t', 'latitude', 'latitude of fire', float],
[
'm', 'maxDistance',
'(optional default=20) max distance in miles from fire', float
],
[
"e", "endTime",
"ending date and time in ISO format (e.g., 2019-02-22T14:34:56 in Pacific time zone)"
],
[
"d", "durationMinutes",
"alternative spec for endTime as start + duration", int
],
[
"g", "gapMinutes",
"override default of 1 minute gap between images to download"
],
["o", "outputDir", "directory to save the output image"],
]
args = collect_args.collectArgs(
reqArgs,
optionalArgs=optArgs,
parentParsers=[goog_helper.getParentParser()])
googleServices = goog_helper.getGoogleServices(settings, args)
gapMinutes = int(args.gapMinutes) if args.gapMinutes else 1
distanceMiles = float(args.maxDistance if args.maxDistance else 20)
outputDir = args.outputDir if args.outputDir else settings.downloadDir
startTimeDT = dateutil.parser.parse(args.startTime)
if args.endTime:
endTimeDT = dateutil.parser.parse(args.endTime)
elif args.durationMinutes:
durationDelta = datetime.timedelta(seconds=60 * args.durationMinutes)
endTimeDT = startTimeDT + durationDelta
else:
endTimeDT = startTimeDT
assert startTimeDT.year == endTimeDT.year
assert startTimeDT.month == endTimeDT.month
assert startTimeDT.day == endTimeDT.day
assert endTimeDT >= startTimeDT
if args.cameraID:
assert (not args.latitude) and (not args.longitude)
cameras = [args.cameraID]
else:
assert args.latitude and args.longitude
dbManager = db_manager.DbManager(sqliteFile=settings.db_file,
psqlHost=settings.psqlHost,
psqlDb=settings.psqlDb,
psqlUser=settings.psqlUser,
psqlPasswd=settings.psqlPasswd)
cameras = getNearbyCameras(dbManager, args.latitude, args.longitude,
distanceMiles)
logging.warning('Matched cmaeras: %s', cameras)
camArchives = img_archive.getHpwrenCameraArchives(settings.hpwrenArchives)
allFiles = []
for cameraID in cameras:
camFiles = img_archive.getHpwrenImages(googleServices, settings,
outputDir, camArchives,
cameraID, startTimeDT,
endTimeDT, gapMinutes)
if camFiles:
allFiles += camFiles
if allFiles:
logging.warning('Found %d files.', len(allFiles))
else:
logging.error('No filed matched')