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Merge pull request #24 from pyronear/alert-samples
Alert samples
2 parents 037768b + 02d19a1 commit d2c3f16

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‎.gitignore‎

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#minio stuff
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data/minio/.minio.sys/
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data/.Trash-0
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containers/notebooks/app/.Trash-0
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.DS_STORE
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data/alert_samples/
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data/triangulated_sequences/

‎containers/notebooks/Dockerfile‎

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# Use an official Python runtime as a parent image
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FROM python:3.8
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FROM python:3.11
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# Set the working directory to /app
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WORKDIR /app

‎containers/notebooks/app/Download_Sequences_from_a_DistantAlertAPI.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"id": "649157c6-0ce3-4324-a7b6-15c911ddaf36",
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"metadata": {},
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"outputs": [],
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"source": [
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"SEQUENCE_ID_LIST = [13802, 9456]\n",
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"BASE_DIRECTORY = \"alerts\" # directory where to put sequences data"
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"SEQUENCE_ID_LIST = [15462, 15463, 15561, 15526, 13880, 13572, 13537, 12997, 12562, 15376, 15526]\n",
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"BASE_DIRECTORY = \"../data/alert_samples\" # directory where to put sequences data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 2,
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"id": "4e511d97-245c-45cc-9216-a16d31b663aa",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 3,
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"id": "ac07ba29-68d0-42d2-bafe-e94d961ec6c2",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d3c12b1d-54f1-4d8d-b591-dc04ecc35db2",
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"execution_count": 4,
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"id": "07192f5f-9a69-41a4-9a97-1f1fcefaaf5b",
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"metadata": {},
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"outputs": [],
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"source": [
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"for seq_id in SEQUENCE_ID_LIST: \n",
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" sequences = api_client.fetch_sequences_detections(sequence_id=seq_id).json()\n",
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"def dl_seqs_in_target_dir(sequence_id_list, target_dir, api_client):\n",
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" \"\"\"\n",
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" Download sequences from sequence_id_list to target_dir, using an instanciated api_client (of distant Pyronear alert API)\n",
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"\n",
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" cam_name = [item['name'] for item in cameras if item['id'] == sequences[0]['camera_id']][0]\n",
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" created_at_rounded = sequences[0][\"created_at\"].split('.')[0].replace(':', '-').replace('T', '_')\n",
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" \"\"\"\n",
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" \n",
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" print(f\"== Download Alerts data for sequence ID {seq_id} - camera {cam_name} at {created_at_rounded}\")\n",
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" for seq_id in sequence_id_list: \n",
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" sequences = api_client.fetch_sequences_detections(sequence_id=seq_id, limit=10, desc=False).json()\n",
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" \n",
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" alert_dir = os.path.join(f\"{cam_name}_{created_at_rounded}\")\n",
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" image_dir = os.path.join(base_dir,alert_dir, \"images\")\n",
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" pred_dir = os.path.join(base_dir, alert_dir, \"labels_predictions\")\n",
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" os.makedirs(image_dir, exist_ok=True)\n",
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" os.makedirs(pred_dir, exist_ok=True)\n",
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"\n",
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" for seq in sequences:\n",
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" cam_name = [item['name'] for item in cameras if item['id'] == sequences[0]['camera_id']][0]\n",
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" created_at_rounded = sequences[0][\"created_at\"].split('.')[0].replace(':', '-').replace('T', '_')\n",
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" cam_id_distant_api = sequences[0][\"camera_id\"]\n",
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" print(f\"== Download Alerts data for sequence ID {seq_id} - camera {cam_name} at {created_at_rounded}\")\n",
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" \n",
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" # bbox\n",
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" #yolo_format_bbox = ' '.join(map(str,ast.literal_eval(seq[\"bboxes\"])[0]))\n",
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" bboxes = seq[\"bboxes\"]\n",
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" alert_dir = os.path.join(f\"{cam_id_distant_api}_{cam_name}_{created_at_rounded}\")\n",
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" image_dir = os.path.join(target_dir,alert_dir, \"images\")\n",
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" pred_dir = os.path.join(target_dir, alert_dir, \"labels_predictions\")\n",
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" os.makedirs(image_dir, exist_ok=True)\n",
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" os.makedirs(pred_dir, exist_ok=True)\n",
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" \n",
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" for seq in sequences:\n",
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" \n",
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" # bbox\n",
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" #yolo_format_bbox = ' '.join(map(str,ast.literal_eval(seq[\"bboxes\"])[0]))\n",
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" bboxes = seq[\"bboxes\"]\n",
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" \n",
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" bbox_file_name = seq[\"bucket_key\"][:-4] + \".txt\"\n",
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" \n",
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" with open(os.path.join(target_dir, alert_dir, \"labels_predictions\",bbox_file_name), 'w') as f:\n",
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" f.write(bboxes)\n",
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" \n",
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" url = seq['url']\n",
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" nom_fichier = seq[\"bucket_key\"]\n",
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" # image\n",
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" response = requests.get(url, stream=True)\n",
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" if response.status_code == 200:\n",
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" full_img_path = os.path.join(image_dir, nom_fichier)\n",
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" with open(full_img_path, 'wb') as f:\n",
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" for chunk in response.iter_content(1024):\n",
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" f.write(chunk)\n",
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" else:\n",
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" print(f\"Error during download.\")\n",
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" print(\"Download complete\")\n",
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" "
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]
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},
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{
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"cell_type": "markdown",
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"id": "9503b5d5-9930-4c9e-9fbe-1eb1e563fd44",
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"metadata": {},
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"source": [
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"# Download sequences from SEQUENCE_ID_LIST list"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "b2d033e9-7ce2-4cf4-995e-01ea2c15e235",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"== Download Alerts data for sequence ID 15462 - camera serre-de-barre-01 at 2025-09-29_13-56-58\n",
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"== Download Alerts data for sequence ID 15463 - camera brison-03 at 2025-09-29_13-58-36\n",
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"== Download Alerts data for sequence ID 15561 - camera pouncho-agast-01 at 2025-10-01_06-18-57\n",
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"== Download Alerts data for sequence ID 15526 - camera pouncho-agast-01 at 2025-09-30_15-29-49\n",
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"== Download Alerts data for sequence ID 13880 - camera fontaneilles-01 at 2025-09-04_07-34-32\n",
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"== Download Alerts data for sequence ID 13572 - camera pouncho-agast-01 at 2025-08-29_06-59-39\n",
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"== Download Alerts data for sequence ID 13537 - camera pouncho-agast-01 at 2025-08-28_15-31-17\n",
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"== Download Alerts data for sequence ID 12997 - camera pouncho-agast-01 at 2025-08-17_15-52-27\n",
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"== Download Alerts data for sequence ID 12562 - camera pouncho-agast-01 at 2025-08-06_12-32-09\n",
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"== Download Alerts data for sequence ID 15376 - camera pouncho-agast-02 at 2025-09-28_10-52-39\n",
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"== Download Alerts data for sequence ID 15526 - camera pouncho-agast-01 at 2025-09-30_15-29-49\n",
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"Download complete\n"
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]
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}
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],
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"source": [
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"single_alerts = os.path.join(BASE_DIRECTORY, \"single_sequences\")\n",
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"os.makedirs(single_alerts, exist_ok=True)\n",
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"\n",
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" bbox_file_name = seq[\"bucket_key\"][:-4] + \".txt\"\n",
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" \n",
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" with open(os.path.join(base_dir, alert_dir, \"labels_predictions\",bbox_file_name), 'w') as f:\n",
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" f.write(bboxes)\n",
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"dl_seqs_in_target_dir(SEQUENCE_ID_LIST, single_alerts, api_client)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e9d109db-324c-4268-bae6-27c5960def55",
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"metadata": {},
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"source": [
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"## Download triangulated alerts\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "68a2cff8-f847-4e6c-8c74-37b7ecffc9af",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"== Download Alerts data for sequence ID 10535 - camera moret-sur-loing-01 at 2025-07-14_11-22-05\n",
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"== Download Alerts data for sequence ID 10537 - camera nemours-02 at 2025-07-14_11-24-10\n",
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"== Download Alerts data for sequence ID 10538 - camera croix-augas-02 at 2025-07-14_11-24-31\n",
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"== Download Alerts data for sequence ID 15462 - camera serre-de-barre-01 at 2025-09-29_13-56-58\n",
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"== Download Alerts data for sequence ID 15463 - camera brison-03 at 2025-09-29_13-58-36\n",
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"Download complete\n"
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]
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}
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],
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"source": [
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"\n",
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" url = seq['url']\n",
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" nom_fichier = seq[\"bucket_key\"]\n",
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" # image\n",
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" response = requests.get(url, stream=True)\n",
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" if response.status_code == 200:\n",
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" full_img_path = os.path.join(image_dir, nom_fichier)\n",
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" with open(full_img_path, 'wb') as f:\n",
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" for chunk in response.iter_content(1024):\n",
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" f.write(chunk)\n",
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" else:\n",
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" print(f\"Error during download.\")"
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"TRIANGULATED_SEQUENCE_LIST = [10535, 10537, 10538, 15462, 15463]\n",
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"TRIANGULATED_DIRECTORY= \"triangulated_sequences\"\n",
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"triangulated_dir = os.path.join(BASE_DIRECTORY, TRIANGULATED_DIRECTORY)\n",
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"os.makedirs(triangulated_dir, exist_ok=True)\n",
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"\n",
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"dl_seqs_in_target_dir(TRIANGULATED_SEQUENCE_LIST, triangulated_dir, api_client)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ffd56f84-ec77-4843-837a-06de85232c94",
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"metadata": {},
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"outputs": [],
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"source": []
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"metadata": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.20"
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"version": "3.13.7"
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}
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},
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"nbformat": 4,

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