{"id":14959125,"url":"https://github.com/cloudwiser/objectdetectionrpizero","last_synced_at":"2025-10-24T16:31:16.608Z","repository":{"id":83242603,"uuid":"176837012","full_name":"cloudwiser/ObjectDetectionRPiZero","owner":"cloudwiser","description":"TensorFlow Lite object detection example for Raspberry Pi Zero","archived":false,"fork":false,"pushed_at":"2019-11-10T18:39:57.000Z","size":5532,"stargazers_count":26,"open_issues_count":1,"forks_count":7,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-01-31T03:12:18.496Z","etag":null,"topics":["armv6","cnn-for-visual-recognition","mobilenet-ssd","object-detection","raspberry-pi-zero","raspberry-pi-zero-w","ssd-mobilenet","tensorflow-examples","tensorflow-lite"],"latest_commit_sha":null,"homepage":null,"language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cloudwiser.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-03-21T00:15:27.000Z","updated_at":"2024-10-21T08:14:31.000Z","dependencies_parsed_at":null,"dependency_job_id":"85d39bf7-f15b-495c-9a5a-7cbd4fd3f0d6","html_url":"https://github.com/cloudwiser/ObjectDetectionRPiZero","commit_stats":{"total_commits":23,"total_committers":1,"mean_commits":23.0,"dds":0.0,"last_synced_commit":"a5bb13feec7648ca48856609e17062810f099488"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cloudwiser%2FObjectDetectionRPiZero","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cloudwiser%2FObjectDetectionRPiZero/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cloudwiser%2FObjectDetectionRPiZero/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cloudwiser%2FObjectDetectionRPiZero/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cloudwiser","download_url":"https://codeload.github.com/cloudwiser/ObjectDetectionRPiZero/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":237999678,"owners_count":19399920,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["armv6","cnn-for-visual-recognition","mobilenet-ssd","object-detection","raspberry-pi-zero","raspberry-pi-zero-w","ssd-mobilenet","tensorflow-examples","tensorflow-lite"],"created_at":"2024-09-24T13:18:53.065Z","updated_at":"2025-10-24T16:31:13.783Z","avatar_url":"https://github.com/cloudwiser.png","language":"C++","readme":"\u003cimg align=\"left\" width=\"120\" height=\"120\" src=\"https://avatars0.githubusercontent.com/u/15658638?s=200\u0026v=4\"\u003e\n\n### TensorFlow Lite : label_image object detection on Raspberry Pi Zero W\n\nThis is a follow-on to compiling TensorFlow Lite for the Raspberry Pi Zero W as detailed at https://github.com/cloudwiser/TensorFlowLiteRPIZero\n\nHaving got the C++ `minimal` example code compiled, this extends the `label_image` example to demonstrate object detection and bounding box extraction using the SSD Mobilenet model trained against the COCO traning set\n\nCopy the content in the `./example`, `./make` and `./bin` sub-directories of this repo to the equivalent paths in your local `./tensorflow/tensorflow/lite/...` directory structure (after backing up the original content)\n\nPlease note that `label_image` has not been tested with other quantized or non-quantized models and it expects 1 input tensor and 4 output tensors...so running it with other models may either fail this test and/or cause a runtime error during model load or invocation\n\nIf this does occur, it should be a case of adjusting the input and output tensor size checks and ensuring the correct handling of TfLite `float` or `uint8_t` output tensors\n\nOnce you have installed (and amended) the code, build it via...\n\n```sh\n$ cd ~/tensorflow/tensorflow/lite/tools/make/\n\n$ ./build_rpi_armv6_label_image.sh\n```\n\nand then run `label_image` as follows. Note: the `-o 1` option writes the output image (with any above-threshold bounding boxes rendered) to an out file of the format `out_\u003cinput_filename\u003e` \n\n```sh\n$ cd ~/tensorflow/tensorflow/lite/tools/make/gen/rpi_armv6/bin\n\n$ ./label_image -i fruit.bmp -m ./models/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29/detect.tflite -l ./models/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29/labelmap.txt -v 1\n\n$ ./label_image -i orange_banana_apple.bmp -m ./models/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29/detect.tflite -l ./models/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29/labelmap.txt -o 1\n```\n\nTypical inference speeds for the sample `orange_banana_apple.bmp` test image provided is ~7000 ms on a Raspberry Pi Zero W\n\nRun `label_image` with `-h` and/or read the source code for the complete set of command line options\n\nThis application is based on the`label_image` example code in the Tensorflow Lite repo at https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/examples/label_image \n \n\n\u003cp align=\"center\"\u003e\n  \u003cimg height=\"186px\" width=\"300px\" border=\"2\" src=\"./assets/out_orange_banana_apple.bmp\"/\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003eSample BMP output showing MS-COCO objects detected above the set threshold\u003cp align=\"center\"\u003e\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcloudwiser%2Fobjectdetectionrpizero","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcloudwiser%2Fobjectdetectionrpizero","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcloudwiser%2Fobjectdetectionrpizero/lists"}