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Merge pull request #40 from sdsc-ordes/fix/timezones
Browse files- src/input/input_handling.py +25 -6
- src/input/input_observation.py +15 -4
- src/input/input_validator.py +22 -0
- tests/test_input_observation.py +12 -6
src/input/input_handling.py
CHANGED
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@@ -12,7 +12,7 @@ import cv2
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import numpy as np
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from input.input_observation import InputObservation
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-
from input.input_validator import get_image_datetime, is_valid_email, is_valid_number, get_image_latlon
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m_logger = logging.getLogger(__name__)
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m_logger.setLevel(logging.INFO)
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@@ -206,6 +206,7 @@ def metadata_inputs_one_file(file:UploadedFile, image_hash:str, dbg_ix:int=0) ->
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author_email = st.session_state["input_author_email"]
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filename = file.name
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image_datetime_raw = get_image_datetime(file)
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latitude0, longitude0 = get_image_latlon(file)
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msg = f"[D] {filename}: lat, lon from image metadata: {latitude0}, {longitude0}"
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m_logger.debug(msg)
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@@ -247,19 +248,37 @@ def metadata_inputs_one_file(file:UploadedFile, image_hash:str, dbg_ix:int=0) ->
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# 5. Date/time
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## first from image metadata
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if image_datetime_raw is not None:
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-
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else:
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-
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## either way, give user the option to enter manually (or correct, e.g. if camera has no rtc clock)
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date = viewcontainer.date_input("Date for "+filename, value=date_value, key=f"input_date_{image_hash}")
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time = viewcontainer.time_input("Time for "+filename, time_value, key=f"input_time_{image_hash}")
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observation = InputObservation(image=image, latitude=latitude, longitude=longitude,
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author_email=author_email, image_datetime_raw=image_datetime_raw,
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-
date=date, time=time,
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uploaded_file=file, image_md5=image_hash
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)
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import numpy as np
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from input.input_observation import InputObservation
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+
from input.input_validator import get_image_datetime, is_valid_email, is_valid_number, get_image_latlon, get_image_timezone
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m_logger = logging.getLogger(__name__)
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m_logger.setLevel(logging.INFO)
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author_email = st.session_state["input_author_email"]
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filename = file.name
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image_datetime_raw = get_image_datetime(file)
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+
image_timezone_raw = get_image_timezone(file)
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latitude0, longitude0 = get_image_latlon(file)
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msg = f"[D] {filename}: lat, lon from image metadata: {latitude0}, {longitude0}"
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m_logger.debug(msg)
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# 5. Date/time
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## first from image metadata
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if image_datetime_raw is not None:
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# if we have a timezone let's use it (but only if we also have datetime)
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time_fmt = '%Y:%m:%d %H:%M:%S'
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if image_timezone_raw is not None:
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image_datetime_raw += f" {image_timezone_raw}"
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time_fmt += ' %z'
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#
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dt = datetime.datetime.strptime(image_datetime_raw, time_fmt)
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date_value = dt.date()
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time_value = dt.time()
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#time_value = datetime.datetime.strptime(image_datetime_raw, '%Y:%m:%d %H:%M:%S').time()
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#date_value = datetime.datetime.strptime(image_datetime_raw, '%Y:%m:%d %H:%M:%S').date()
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else:
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# get current time, with user timezone (or is it server timezone?! TODO: test with different zones)
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dt = datetime.datetime.now().astimezone().replace(microsecond=0)
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time_value = dt.time()
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date_value = dt.date()
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#time_value = datetime.datetime.now().time() # Default to current time
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#date_value = datetime.datetime.now().date()
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## either way, give user the option to enter manually (or correct, e.g. if camera has no rtc clock)
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date = viewcontainer.date_input("Date for "+filename, value=date_value, key=f"input_date_{image_hash}")
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time = viewcontainer.time_input("Time for "+filename, time_value, key=f"input_time_{image_hash}")
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tz_str = dt.strftime('%z') # this is numeric, otherwise the info isn't consistent.
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observation = InputObservation(image=image, latitude=latitude, longitude=longitude,
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author_email=author_email, image_datetime_raw=image_datetime_raw,
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date=date, time=time, timezone=tz_str,
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uploaded_file=file, image_md5=image_hash
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)
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src/input/input_observation.py
CHANGED
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@@ -26,6 +26,8 @@ class InputObservation:
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Date of the observation
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time (datetime.time):
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Time of the observation
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uploaded_file (UploadedFile):
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The uploaded file associated with the observation.
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image_md5 (str):
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@@ -57,6 +59,7 @@ class InputObservation:
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author_email:str=None, image_datetime_raw:str=None,
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date:datetime.date=None,
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time:datetime.time=None,
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uploaded_file:UploadedFile=None, image_md5:str=None):
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self.image = image
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@@ -66,6 +69,7 @@ class InputObservation:
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self.image_datetime_raw = image_datetime_raw
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self.date = date
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self.time = time
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self.uploaded_file = uploaded_file
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self.image_md5 = image_md5
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# attributes that get set after predictions/processing
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@@ -121,7 +125,7 @@ class InputObservation:
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return (
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f"Observation: {_im_str}, {self.latitude}, {self.longitude}, "
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f"{self.author_email}, {self.image_datetime_raw}, {self.date}, "
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f"{self.time}, {self.uploaded_file}, {self.image_md5}"
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)
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def __repr__(self):
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@@ -135,6 +139,7 @@ class InputObservation:
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f"raw timestamp: {self.image_datetime_raw}, "
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f"Date: {self.date}, "
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f"Time: {self.time}, "
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f"Uploaded Filename: {self.uploaded_file}"
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f"Image MD5 hash: {self.image_md5}"
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)
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@@ -158,6 +163,7 @@ class InputObservation:
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self.date == other.date and
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# temporarily skip time, it is followed by the clock and that is always differnt
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#self.time == other.time and
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self.uploaded_file == other.uploaded_file and
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self.image_md5 == other.image_md5
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)
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@@ -167,7 +173,7 @@ class InputObservation:
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# only highlight the differences, if element is the same don't show it
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# have a summary at the top that shows if the observations are the same or not
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def show_diff(self, other):
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"""Show the differences between two observations"""
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differences = []
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if self.image is None or other.image is None:
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@@ -189,6 +195,8 @@ class InputObservation:
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differences.append(f" Date is different. (self: {self.date}, other: {other.date})")
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if self.time != other.time:
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differences.append(f" Time is different. (self: {self.time}, other: {other.time})")
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if self.uploaded_file != other.uploaded_file:
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differences.append(" Uploaded filename is different.")
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if self.image_md5 != other.image_md5:
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@@ -216,6 +224,7 @@ class InputObservation:
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"image_datetime_raw": self.image_datetime_raw,
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"date": str(self.date),
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"time": str(self.time),
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"selected_class": self._selected_class,
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"top_prediction": self._top_predictions[0] if len(self._top_predictions) else None,
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"class_overriden": self._class_overriden,
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@@ -233,12 +242,13 @@ class InputObservation:
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image_datetime_raw=data.get("image_datetime_raw"),
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date=data.get("date"),
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time=data.get("time"),
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uploaded_file=data.get("uploaded_file"),
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image_hash=data.get("image_md5")
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)
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@classmethod
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def from_input(cls, input):
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return cls(
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image=input.image,
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latitude=input.latitude,
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@@ -247,8 +257,9 @@ class InputObservation:
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image_datetime_raw=input.image_datetime_raw,
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date=input.date,
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time=input.time,
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uploaded_file=input.uploaded_file,
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-
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)
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Date of the observation
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time (datetime.time):
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Time of the observation
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timezone (str):
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Timezone of the observation (e.g. +0300)
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uploaded_file (UploadedFile):
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The uploaded file associated with the observation.
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image_md5 (str):
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author_email:str=None, image_datetime_raw:str=None,
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date:datetime.date=None,
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time:datetime.time=None,
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timezone:str=None,
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uploaded_file:UploadedFile=None, image_md5:str=None):
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self.image = image
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self.image_datetime_raw = image_datetime_raw
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self.date = date
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self.time = time
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self.timezone = timezone
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self.uploaded_file = uploaded_file
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self.image_md5 = image_md5
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# attributes that get set after predictions/processing
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return (
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f"Observation: {_im_str}, {self.latitude}, {self.longitude}, "
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f"{self.author_email}, {self.image_datetime_raw}, {self.date}, "
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f"{self.time}, {self.timezone}, {self.uploaded_file}, {self.image_md5}"
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)
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def __repr__(self):
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f"raw timestamp: {self.image_datetime_raw}, "
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f"Date: {self.date}, "
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f"Time: {self.time}, "
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f"Timezone: {self.timezone}, "
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f"Uploaded Filename: {self.uploaded_file}"
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f"Image MD5 hash: {self.image_md5}"
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)
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self.date == other.date and
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# temporarily skip time, it is followed by the clock and that is always differnt
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#self.time == other.time and
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self.timezone == other.timezone and
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self.uploaded_file == other.uploaded_file and
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self.image_md5 == other.image_md5
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)
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# only highlight the differences, if element is the same don't show it
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# have a summary at the top that shows if the observations are the same or not
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def show_diff(self, other: 'InputObservation'):
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"""Show the differences between two observations"""
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differences = []
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if self.image is None or other.image is None:
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differences.append(f" Date is different. (self: {self.date}, other: {other.date})")
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if self.time != other.time:
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differences.append(f" Time is different. (self: {self.time}, other: {other.time})")
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if self.timezone != other.timezone:
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differences.append(f" Timezone is different. (self: {self.timezone}, other: {other.timezone})")
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if self.uploaded_file != other.uploaded_file:
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differences.append(" Uploaded filename is different.")
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if self.image_md5 != other.image_md5:
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"image_datetime_raw": self.image_datetime_raw,
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"date": str(self.date),
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"time": str(self.time),
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"timezone": str(self.timezone),
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"selected_class": self._selected_class,
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"top_prediction": self._top_predictions[0] if len(self._top_predictions) else None,
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"class_overriden": self._class_overriden,
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image_datetime_raw=data.get("image_datetime_raw"),
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date=data.get("date"),
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time=data.get("time"),
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timezone=data.get("timezone"),
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uploaded_file=data.get("uploaded_file"),
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image_hash=data.get("image_md5")
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)
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@classmethod
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def from_input(cls, input: 'InputObservation'):
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return cls(
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image=input.image,
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latitude=input.latitude,
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image_datetime_raw=input.image_datetime_raw,
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date=input.date,
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time=input.time,
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timezone=input.timezone,
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uploaded_file=input.uploaded_file,
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image_md5=input.image_md5
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)
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src/input/input_validator.py
CHANGED
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@@ -84,6 +84,28 @@ def get_image_datetime(image_file:UploadedFile) -> Union[str, None]:
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# TODO: add to logger
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return None
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def decimal_coords(coords:tuple, ref:str) -> Fraction:
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"""
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# TODO: add to logger
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return None
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# function to extract the timezone from image metadata
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def get_image_timezone(image_file:UploadedFile) -> Union[str, None]:
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"""
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Extracts the timezone from the EXIF metadata of an uploaded image file.
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Args:
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image_file (UploadedFile): The uploaded image file from which to extract the timezone.
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Returns:
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str: The timezone as a string if available, otherwise None.
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Raises:
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Warning: If the timezone could not be extracted from the image metadata.
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"""
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try:
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image = Image.open(image_file)
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exif_data = image._getexif()
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if exif_data is not None:
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if ExifTags.Base.OffsetTimeOriginal in exif_data:
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return exif_data.get(ExifTags.Base.OffsetTimeOriginal)
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except Exception as e: # FIXME: what types of exception?
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st.warning(f"Could not extract timezone from image metadata. (file: {image_file.name})")
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def decimal_coords(coords:tuple, ref:str) -> Fraction:
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"""
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tests/test_input_observation.py
CHANGED
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@@ -89,11 +89,12 @@ def test_input_observation_valid(mock_uploadedFile):
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_date="2023-10-10"
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_time="10:10:10"
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-
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-
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date = dt.date()
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time = dt.time()
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-
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## make a random image with dtype uint8 using np.random.randint
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image = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
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image_md5 = 'd1d2515e6f6ac4c5ca6dd739d5143cd4' # 32 hex chars.
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obs = InputObservation(
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image=image,
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latitude=12.34, longitude=56.78, author_email=author_email,
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time=time, date=date,
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uploaded_file=mock_file,
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image_md5=image_md5,
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)
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@@ -116,6 +117,7 @@ def test_input_observation_valid(mock_uploadedFile):
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assert isinstance(obs.time, datetime.time)
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assert str(obs.date) == "2023-10-10"
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assert str(obs.time) == "10:10:10"
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assert obs.uploaded_file.name == image_name
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assert obs.uploaded_file.size == 123456
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@@ -274,16 +276,20 @@ def good_datadict_for_input_observation(mock_uploadedFile) -> dict:
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# set up the good and bad inputs
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_date="2023-10-10"
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_time="10:10:10"
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-
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fname = "test_image.jpg"
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image = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
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-
dt_ok = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S")
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valid_inputs = {
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"author_email": "[email protected]",
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"uploaded_file": mock_uploadedFile(name=fname).get_data(),
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"date": dt_ok.date(),
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"time": dt_ok.time(),
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"image": image,
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"image_md5": 'd1d2515e6f6ac4c5ca6dd739d5143cd4', # 32 hex chars.
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"image_datetime_raw": image_datetime_raw,
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_date="2023-10-10"
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_time="10:10:10"
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| 92 |
+
_timezone = "+04:00"
|
| 93 |
+
image_datetime_raw = _date + " " + _time + " " + _timezone
|
| 94 |
+
dt = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S %z")
|
| 95 |
date = dt.date()
|
| 96 |
time = dt.time()
|
| 97 |
+
tz_str = dt.strftime('%z')
|
| 98 |
## make a random image with dtype uint8 using np.random.randint
|
| 99 |
image = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
|
| 100 |
image_md5 = 'd1d2515e6f6ac4c5ca6dd739d5143cd4' # 32 hex chars.
|
|
|
|
| 102 |
obs = InputObservation(
|
| 103 |
image=image,
|
| 104 |
latitude=12.34, longitude=56.78, author_email=author_email,
|
| 105 |
+
time=time, date=date, timezone=tz_str,
|
| 106 |
uploaded_file=mock_file,
|
| 107 |
image_md5=image_md5,
|
| 108 |
)
|
|
|
|
| 117 |
assert isinstance(obs.time, datetime.time)
|
| 118 |
assert str(obs.date) == "2023-10-10"
|
| 119 |
assert str(obs.time) == "10:10:10"
|
| 120 |
+
assert obs.timezone == tz_str
|
| 121 |
|
| 122 |
assert obs.uploaded_file.name == image_name
|
| 123 |
assert obs.uploaded_file.size == 123456
|
|
|
|
| 276 |
# set up the good and bad inputs
|
| 277 |
_date="2023-10-10"
|
| 278 |
_time="10:10:10"
|
| 279 |
+
_timezone = "+04:00"
|
| 280 |
+
image_datetime_raw = _date + " " + _time + " " + _timezone
|
| 281 |
+
#dt = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S %z")
|
| 282 |
fname = "test_image.jpg"
|
| 283 |
image = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
|
| 284 |
|
| 285 |
+
dt_ok = datetime.datetime.strptime(image_datetime_raw, "%Y-%m-%d %H:%M:%S %z")
|
| 286 |
+
tz_str = dt_ok.strftime('%z')
|
| 287 |
valid_inputs = {
|
| 288 |
"author_email": "[email protected]",
|
| 289 |
"uploaded_file": mock_uploadedFile(name=fname).get_data(),
|
| 290 |
"date": dt_ok.date(),
|
| 291 |
"time": dt_ok.time(),
|
| 292 |
+
"timezone": tz_str,
|
| 293 |
"image": image,
|
| 294 |
"image_md5": 'd1d2515e6f6ac4c5ca6dd739d5143cd4', # 32 hex chars.
|
| 295 |
"image_datetime_raw": image_datetime_raw,
|