Wild demo

README.md

@@ -90,6 +90,3 @@ These scripts rely on the [CameraTraps Repo](https://github.com/microsoft/Camera
 # Processing Batch Images
 Run_batch_images.py can take in an input folder and apply the detector/classifier pipeline to render annotated images along with an output.json file in directory classifications. The output.json contains the final classifications on the cropped images and can be used to compare against a ground truth set. There is also an intermediate output.json which holds the crop detections and is used by the script to crop images, this one can be moved by configuration in the yml file.
 These scripts rely on the [CameraTraps Repo](https://github.com/microsoft/CameraTraps). Download this repo and place it anywhere. Add that path to config. The CameraTraps repo will then be added to the python sys environment variables upon loading an individual script.
-
-# Improvement Efforts
-If you encounter any issues upon install or would like a feature added, create an issue in the issue tracker on this github and we will do our best to accomodate! Specifically we are looking to add new integrations for other types of cellular camera traps.

config/fetch_and_alert.yml

@@ -1,7 +1,11 @@
 #home_dir - path to local cougarvision repo
 home_dir: /home/johnsmith/cougarvision 
+#True to send detections to consumer emails
 email_alerts: True
-er_alerts: True
+#True to send detections to earthranger
+# 1 = email alerts and 2 = earthranger alerts
+email_alerts: True
+er_alerts: True 
 #detector_model - path to detector model
 detector_model: /home/johnsmith/cougarvision/detector_models/megadetector.pt
 #type of detection model expected ["MDV5", "MDV6", "YOLO", "ONNX"]
@@ -13,29 +17,35 @@ checkpoint_frequency: -1
 log_dir: /home/johnsmith/cougarvision/logs/
 #classes - path to the class list for the classifier model
 classes: /home/johnsmith/cougarvision/labels/sw_classes.txt 
+#Run version that allows for images cast to two screens? True/False
+visualize_output: True
+#for visualizing output, folder for cougarvision to put all images
+path_to_unlabeled_output: /path/to/unlabeled/img/folder
+#for visualizing output, folder for cougarvision detections with bounding boxes
+path_to_labeled_output: /path/to/labeled/img/folder
 #the emails that will receive email alerts, can be multiple emails
-consumer_emails: [<insert emails>]
-# the amiul (s) you with to receive the developmemt email alert- contains confidence value of detection
-dev_emails: [<insert emails>] 
+consumer_emails: [your@email.com]
+#emails to recieve daily check-in and confidence of detections 
+dev_emails: [your@email.com] 
 #threshold confidence score 
 confidence: 0.7
 #cpu threads
 threads: 8
-# Web Scraping
 #strike force api url
 strikeforce_api: https://api.strikeforcewireless.com/api/v2/
 #strikeforce wireless username 
-username_scraper: [yourusername.cam@gmail.com]
+username_scraper: yourusername.cam@gmail.com
 #strikeforce wireless password
-password_scraper: [yourpassword]
-#authorization token from Strike Force, can be obtained with login credentials and using strikeforceget.py in /cougarvision_utils folder
-auth_token: ["<insert account token>"]
+password_scraper: yourpassword
+#authorization token from Strike Force
+auth_token: <must get from web dev tools after strikeforcewireless login>
 #save_dir - path to where the images get stored (must create folder)
 save_dir: /home/johnsmith/images/ 
-#dictionary containing the strikeforce unique ID with the actual 4 digit camera name, ID can be obtained using strikeforcegetcameras.py within the /cougarvision_utils folder
-camera_names: {'<strikeforce id>': <camera name>, ...}  
+#dict of camera names and their respective strikeforce wireless ids, these must be retrieved from
+#strikeforce wireless web dev tools in the code and currently the cam names must be 4 chars long 
+camera_names: {'<strikeforceid>': <camera name>, '<strikeforceid>': <camera name>...}  
 #animals that the detector will send alerts for if detected (from class list)
-alert_targets: [cougar, bobcat, skunk, deer, dog, coyote]
+alert_targets: [cougar, bobcat, skunk, deer, dog, coyote, rabbit, elephant]
 #checkn_interval - time interval between still-alive emails to let us know no errors have crashed
 #cougarvision if it's running constantly
 checkin_interval: 24

cougarvision_utils/detect_img.py

@@ -12,13 +12,15 @@
 from io import BytesIO
 from datetime import datetime as dt
 import re
+import os
 from PIL import Image
 from animl import classification, split
 from animl import detection
 from sageranger import is_target, attach_image, post_event
 
 from cougarvision_utils.cropping import draw_bounding_box_on_image
 from cougarvision_utils.alert import smtp_setup, send_alert
+from cougarvision_visualize.visualize_helper import get_last_file_number
 
 
 def detect(images, config):  # pylint: disable=too-many-locals
@@ -110,6 +112,21 @@ def detect(images, config):  # pylint: disable=too-many-locals
                     image_bytes = BytesIO()
                     img.save(image_bytes, format="JPEG")
                     img_byte = image_bytes.getvalue()
+
+                    # not sure if labeled_img is meant to point at Images
+                    labeled_img = config.path_to_labeled_output
+                    if config.visualize_output is True:
+                        os.makedirs(labeled_img, exist_ok=True)
+                        last_file_number = get_last_file_number(labeled_img)
+                        new_file_number = last_file_number + 1
+                        name = images[idx][2]
+                        name = name.split('/')[-1]
+                        #new_file_name = f"{labeled_img + name}/image_{new_file_number}.jpg"
+                        new_file_name = f"{labeled_img + "/" + name}"
+
+                        with open(new_file_name, "wb") as folder:
+                            folder.write(img_byte)
+
                     cam_name = cougars.at[idx, 'cam_name']
                     er_alerts = config.er_alerts
                     if label in config.alert_targets and er_alerts is True:

cougarvision_utils/get_images.py

@@ -18,6 +18,9 @@
 import logging
 import requests
 import numpy as np
+import os.path
+import os
+from cougarvision_visualize.visualize_helper import get_last_file_number
 
 # pylint: disable=pointless-string-statement
 """
@@ -26,30 +29,29 @@
 request <- "cameras"
 parameters <- ""
 
-#recent photo count
+recent photo count
 request <- "photos/recent/count"
 parameters <- ""
 
-#get recent photos across cameras
+get recent photos across cameras
 request <- "photos/recent"
 parameters <- "limit=100"
 
-#get photos from specific camera (will need to loop through pages)
+get photos from specific camera (will need to loop through pages)
 request <- "photos"
 parameters <- "page=3&sort_date=desc&camera_id[]=59681"
 
-#get photos from specific camera filtered by date (will need
-# to loop through pages)
+get photos from specific camera filtered by date (will need
+to loop through pages)
 request <- "photos"
 parameters <- "page=1&sort_date=desc&camera_id[]=
-#60272&date_start=2022-09-01&date_end=2022-10-07"
+60272&date_start=2022-09-01&date_end=2022-10-07"
 
-#get subscriptions
+get subscriptions
 request <- "subscriptions"
 parameters <- ""
 """
 
-
 def request_strikeforce(username, auth_token, base, request, parameters):
     """Strikeforce API call request.
 
@@ -69,7 +71,7 @@ def request_strikeforce(username, auth_token, base, request, parameters):
             request fails.
     """
     call = base + request + "?" + parameters
-
+    
     # if there is no internet connection try 5 times before raising exception
     max_retries = 5
     for attempt in range(max_retries):
@@ -148,21 +150,37 @@ def fetch_image_api(config):  # pylint: disable=too-many-locals
             print(info)
 
             try:
-
                 camera = config.camera_names[photo['relationships']
                                              ['camera']['data']['id']]
             except KeyError:
-                logging.warning('Cannot retrieve photo from camera\
-                as there is no asssociated ID in the config file')
+                logging.warning('skipped img: no associated cam ID')
                 continue
             newname = config.save_dir + camera
             newname += "_" + str(info['id'])
+            # 2023-10-29 16:17:20 -0700
+            date_time = (str(info['local_time'])).rsplit(' ',1)[0]
+            newname += "_" + date_time
             newname += "_" + info['file_thumb_filename']
+
             # native extension from strikeforce is .JPG.jpeg for some reason
             stripped_name = newname.replace(".JPG.jpeg", ".jpg")
             urllib.request.urlretrieve(info['file_thumb_url'], stripped_name)
             new_photos.append([photo['id'],
                                info['file_thumb_url'], stripped_name])
+
+            # not sure what unlabeled output should be
+            unlabeled_img = config.path_to_unlabeled_output
+            if config.visualize_output is True:
+                os.makedirs(unlabeled_img, exist_ok=True)
+                newname = unlabeled_img + 'image'
+                new_file_num = get_last_file_number(unlabeled_img)
+                new_file_num = new_file_num + 1
+               # new_file_num = str(new_file_num)
+                newname = os.path.join(unlabeled_img, f"image_{new_file_num}.jpg")
+               # newname += "_" + new_file_num
+                urllib.request.urlretrieve(info['file_thumb_url'], newname)
+
+
 
     new_photos = np.array(new_photos)
     if len(new_photos) > 0:  # update last image

cougarvision_utils/get_info.py

@@ -51,6 +51,9 @@ class ConfigInfo:
     auth_token: str
     id_path: str
     password_scraper: str
+    visualize_output: str
+    path_to_unlabeled_output: str
+    path_to_labeled_output: str
 
     # runtime fields not apart of inital constructor
     classifier_model_load: Any = field(init=False)
@@ -70,3 +73,11 @@ def __post_init__(self):
         self.detector_model_load = load_detector(
             self.detector_model, self.detector_model_type
         )
+
+
+@dataclass
+class display_info:
+     path_to_unlabeled_output: str
+     path_to_labeled_output: str
+     save_dir: str
+     display_num: int