Closed deepukr007 closed 3 months ago
Hello there! 👋
Calculating the mAP for your two-stage method involves evaluating how well your detection model identifies objects (birds in your case) and how accurately your classification model classifies these detected objects into their respective bird classes.
A simplified approach would be as follows:
Both steps (detection and classification) are crucial; mispredictions in either step affect the final accuracy.
Here's a pseudo-code snippet to illustrate the evaluation process:
# Assuming 'detector' is your trained detection model and 'classifier' is your trained classification model.
for image in test_images:
# Step 1: Detect objects
detections = detector.detect(image)
for box in detections:
# Step 2: Crop and classify
crop = image.crop(box.coordinates)
label = classifier.predict(crop)
# Compile your prediction: [image_id, x_min, y_min, x_max, y_max, confidence, predicted_label]
predictions.append([image_id] + box.coordinates + [box.confidence] + [label])
# Step 3: Prepare your ground truth in a similar format for comparison
# Step 4: Use a mAP calculation tool/script, passing the 'predictions' and ground truth
mAP = calculate_mAP(predictions, ground_truth)
Make sure your predictions and ground truth data are correctly formatted for the mAP calculation tool you choose. There are several open-source tools and libraries available for calculating mAP, such as COCO API or Pycocotools.
Hope this helps! Let us know if you have further questions. 🦜
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Question
Hi, I am working on small object detection and to make the whole process robust. I am first training Yolo for detecting all the classes (different types of birds ) as a single class ( bird ). I am also training a classification model for classifying the different birds given the cropped images of birds from the main image.
Now since I have 2 models ready , While inferencing I will first run a detection model , get boxes , crop the objects and pass it through the classifier and relabel the image.
I am getting mAP for detection model and Validation accuracy for classfication model. Now I want to run this above mentioned pipeline and give the actual mAP, what should be my approach ?
Thanks in advance
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