Download seq from distant api

.env.test

@@ -20,3 +20,8 @@ S3_REGION=us-east-1
 
 DB_UI_MAIL=dummy@pyronear.com
 DB_UI_PWD=strong-password
+
+# only usefull to download some real sequences from real/distant Pyronear alert API
+DISTANT_API_URL=''
+DISTANT_ALERT_API_LOGIN=''
+DISTANT_ALERT_API_PASSWORD=''

containers/notebooks/app/Download_Sequences_from_a_DistantAlertAPI.ipynb

@@ -0,0 +1,140 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a1c721ae-469b-48d7-a1df-3cd24623b3ee",
+   "metadata": {},
+   "source": [
+    "# Intro\n",
+    "\n",
+    "This notebook aims at downloading sequences infos(images and bboxes) from a Distant/Real Pyronear Alert API isntance in order to recreate alerts/sequences with ease in local dev environnement\n",
+    "\n",
+    "You need to have accesses to a distant api and provide ```DISTANT_API_URL```, ```DISTANT_ALERT_API_LOGIN```, ```DISTANT_ALERT_API_PASSWORD```\n",
+    "\n",
+    "And obvisouly, fill ```SEQUENCE_ID_LIST``` with the sequence id you want in order to download related data\n",
+    "\n",
+    "\n",
+    "If you do not have anything from above, do not worry, you can use the notebook \"send_real_alerts\" to send some alerts to local env dev"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "649157c6-0ce3-4324-a7b6-15c911ddaf36",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "SEQUENCE_ID_LIST = [13802, 9456]\n",
+    "BASE_DIRECTORY = \"alerts\" # directory where to put sequences data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4e511d97-245c-45cc-9216-a16d31b663aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "from dotenv import load_dotenv\n",
+    "import os\n",
+    "\n",
+    "from pyroclient import Client\n",
+    "\n",
+    "load_dotenv(\"../.env\")\n",
+    "DISTANT_API_URL = os.environ.get(\"DISTANT_API_URL\")\n",
+    "DISTANT_ALERT_API_LOGIN = os.environ.get(\"DISTANT_ALERT_API_LOGIN\")\n",
+    "DISTANT_ALERT_API_PASSWORD = os.environ.get(\"DISTANT_ALERT_API_PASSWORD\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ac07ba29-68d0-42d2-bafe-e94d961ec6c2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "token = requests.post(\n",
+    "    f\"{DISTANT_API_URL}api/v1/login/creds\",\n",
+    "    data={\"username\": DISTANT_ALERT_API_LOGIN, \"password\": DISTANT_ALERT_API_PASSWORD},\n",
+    "    timeout=5,\n",
+    ").json()['access_token']\n",
+    "\n",
+    "api_client = Client(token, DISTANT_API_URL)\n",
+    "\n",
+    "# get cameras -> in order to get cam name from cam id\n",
+    "cameras = api_client.fetch_cameras().json()\n",
+    "\n",
+    "# define base directory\n",
+    "base_dir = os.path.join(BASE_DIRECTORY)\n",
+    "os.makedirs(base_dir, exist_ok=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d3c12b1d-54f1-4d8d-b591-dc04ecc35db2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for seq_id in SEQUENCE_ID_LIST: \n",
+    "    sequences = api_client.fetch_sequences_detections(sequence_id=seq_id).json()\n",
+    "\n",
+    "    cam_name = [item['name'] for item in cameras if item['id'] == sequences[0]['camera_id']][0]\n",
+    "    created_at_rounded = sequences[0][\"created_at\"].split('.')[0].replace(':', '-').replace('T', '_')\n",
+    "    \n",
+    "    print(f\"== Download Alerts data for sequence ID {seq_id} - camera {cam_name} at {created_at_rounded}\")\n",
+    "    \n",
+    "    alert_dir = os.path.join(f\"{cam_name}_{created_at_rounded}\")\n",
+    "    image_dir = os.path.join(base_dir,alert_dir,  \"images\")\n",
+    "    pred_dir = os.path.join(base_dir, alert_dir, \"labels_predictions\")\n",
+    "    os.makedirs(image_dir, exist_ok=True)\n",
+    "    os.makedirs(pred_dir, exist_ok=True)\n",
+    "\n",
+    "    for seq in sequences:\n",
+    "        \n",
+    "        # bbox\n",
+    "        #yolo_format_bbox = ' '.join(map(str,ast.literal_eval(seq[\"bboxes\"])[0]))\n",
+    "        bboxes = seq[\"bboxes\"]\n",
+    "\n",
+    "        bbox_file_name = seq[\"bucket_key\"][:-4] + \".txt\"\n",
+    "        \n",
+    "        with open(os.path.join(base_dir, alert_dir, \"labels_predictions\",bbox_file_name), 'w') as f:\n",
+    "            f.write(bboxes)\n",
+    "\n",
+    "        url = seq['url']\n",
+    "        nom_fichier = seq[\"bucket_key\"]\n",
+    "        # image\n",
+    "        response = requests.get(url, stream=True)\n",
+    "        if response.status_code == 200:\n",
+    "            full_img_path = os.path.join(image_dir, nom_fichier)\n",
+    "            with open(full_img_path, 'wb') as f:\n",
+    "                for chunk in response.iter_content(1024):\n",
+    "                    f.write(chunk)\n",
+    "        else:\n",
+    "            print(f\"Error during download.\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.20"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}