From 77d6a1e60837778775ca524fa898b3c9726ce4ea Mon Sep 17 00:00:00 2001 From: rohanmarwaha Date: Fri, 9 Feb 2024 00:14:19 +0530 Subject: [PATCH 01/22] Add pest detection API: This introduces a new pest detection feature, leveraging a custom-trained YOLOv8n model. It includes the PestDetection class for processing images, an endpoint for handling pest detection requests, and integration with the Ingest class for running pest detection on images and uploading annotated images to S3. --- ai_ta_backend/main.py | 33 ++++++++++++ ai_ta_backend/pest_detection.py | 44 +++++++++++++++ ai_ta_backend/pest_detection_model_weights.pt | Bin 0 -> 6200153 bytes ai_ta_backend/vector_database.py | 51 ++++++++++++++++++ 4 files changed, 128 insertions(+) create mode 100644 ai_ta_backend/pest_detection.py create mode 100644 ai_ta_backend/pest_detection_model_weights.pt diff --git a/ai_ta_backend/main.py b/ai_ta_backend/main.py index 55b39ebf..550f5f14 100644 --- a/ai_ta_backend/main.py +++ b/ai_ta_backend/main.py @@ -620,6 +620,39 @@ def getTopContextsWithMQR() -> Response: response.headers.add('Access-Control-Allow-Origin', '*') return response +@app.route('/pest-detection', methods=['POST']) +def pest_detection(): + """ + Endpoint to detect pests in an image using the pest detection plugin. + Expects a JSON payload with an 'image_url' key pointing to the image to be processed. + + Returns: + Response: A response containing the annotated image with bounding boxes and class labels. + """ + data = request.get_json() + image_urls = data.get('image_urls', []) + + if not image_urls: + abort(400, description="Missing 'image_urls' parameter in the request body.") + + # Deduplicate the image urls + image_urls = list(set(image_urls)) + + try: + posthog = Posthog(project_api_key=os.environ['POSTHOG_API_KEY'], host='https://app.posthog.com') + posthog.capture('distinct_id_of_the_user', event='pest_detection_invoked', properties={'image_urls': image_urls}) + ingester = Ingest() + # Call the pest detection plugin function + annotated_images = ingester.run_pest_detection(image_urls) + del ingester + posthog.shutdown() + # Send the annotated image urls in the response + response = jsonify(annotated_images) + response.headers.add('Access-Control-Allow-Origin', '*') + + return response + except Exception as e: + abort(500, description=str(e)) if __name__ == '__main__': app.run(debug=True, port=int(os.getenv("PORT", default=8000))) # nosec -- reasonable bandit error suppression diff --git a/ai_ta_backend/pest_detection.py b/ai_ta_backend/pest_detection.py new file mode 100644 index 00000000..f2899d89 --- /dev/null +++ b/ai_ta_backend/pest_detection.py @@ -0,0 +1,44 @@ +from typing import List +from PIL import Image +from ultralytics import YOLO +from pathlib import Path + +class PestDetection: + """ + AIFARMS CropWizard Plugin for Pest Detection and Classification + """ + + def __init__(self): + # Load a custom trained YOLOv8n model for pest detection and classification By Aditya Sengupta + # Google Colab Implementation: + # https://colab.research.google.com/drive/1GO-lw2PJtVewlA-xhBfgBLId8v4v-BE2?usp=sharing + + # The model weights can be found at: + # https://www.dropbox.com/scl/fi/xf8wi0jy72kuk3xl47dnx/Aditya-Pest-Detection-YOLO-V1.pt + self.model = YOLO(Path.cwd() / 'ai_ta_backend/pest_detection_model_weights.pt') + + def detect_pests(self, image_paths: List[str]) -> List[Image.Image]: + # Run inference + results = self.model(image_paths) # results object with inference results + + annotated_images = [] + + # Extract annotated images from the results object + # Flatten the results object to get the annotated images for each input image + for result_set in results: + for r in result_set: + im_array = r.plot() # plot a BGR numpy array of predictions + im = Image.fromarray(im_array[..., ::-1]) # RGB PIL image (annotated with bounding boxes and class labels) + annotated_images.append(im) + + return annotated_images + +if __name__ == '__main__': + # Sample usage with multiple images + plugin = PestDetection() + image_urls = ['https://www.arborday.org/trees/health/pests/images/figure-whiteflies-1.jpg', 'https://www.arborday.org/trees/health/pests/images/figure-japanese-beetle-3.jpg'] + output = plugin.detect_pests(image_urls) + + # Print annotated images + for image in output: + image.show() \ No newline at end of file diff --git a/ai_ta_backend/pest_detection_model_weights.pt b/ai_ta_backend/pest_detection_model_weights.pt new file mode 100644 index 0000000000000000000000000000000000000000..88d3a92975c668467e0215c1f3769ea7be4082bb GIT binary patch literal 6200153 zcmb5X2VfLc_x>NcgpPt;QBjEnNkW-C@^b#`l{X-7 zYHf44-L&ekdgz>44SS62mv>Ox|5`gH6L~`>b-~MP=QP#SB|3~=h5sh?gn_TFnqD6^ z);2dMI*xTa&2E}j+mPr~)6x)Hb;JCyzNUF-W8=`Ux_MS}{%*BlZB1C;)HsHF3 zz9!61bT0@J`L2VisV&o|bMGE?H1?ddK6`0wYOI_vD&J-rlwiViTe4RUv@ZkSg+zqzWW8gZJISl{iq!KD829kV`c=$bd0w9#st|1;#qZr4GR`f=Ch zusW=*nufspU~J-AH=Q(~O>1_j&DAPx=uA=lhxEQ<9yT5nx@7Oc~xuq<7*Qw$bkB4WZu@uyls++ZHLr# zTUxh1Y?%>BtVR8#uO3$Eu`G2cxu3u`a7qP|NES zv5GpyX8SrtV23)nxMQ7M*r`tMdgmdNIv{w%61%jWG%*+E=8tM>oSUB*f%m;@GBGmt 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