Create README.md

README.md

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+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/model-cards
+{}
+---
+
+# object-detection: detr-finetuned-thermal-dogs-and-people
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This model is a fine-tuned version of [DETR](https://huggingface.co/facebook/detr-resnet-50) on the Roboflow [Thermal Dogs and People](https://public.roboflow.com/object-detection/thermal-dogs-and-people/1) dataset.
+It achieves the following results on the evaluation set:
+
+```
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.681
+ Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.870
+ Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.778
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.189
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.489
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.720
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.641
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.733
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.746
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.500
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.542
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.794
+```
+## Intended purpose
+
+Main purpose for this model are solely for learning purposes.
+
+Thermal images have a wide array of applications: monitoring machine performance, seeing in low light conditions, and adding another dimension to standard RGB scenarios. Infrared imaging is useful in security, wildlife detection,and hunting / outdoors recreation.
+
+## Training and evaluation data
+
+Data can be seen at [Weights and Biases](https://wandb.ai/faldeus0092/thermal-dogs-and-people/runs/zjt8bp9x?workspace=user-faldeus0092)
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-4
+- lr_backbone: 1e-5
+- weight_decay: 1e-4
+- optimizer: AdamW
+- train_batch_size: 4
+- eval_batch_size: 2
+- train_set: 142
+- test_set: 41
+- num_epochs: 68
+
+### Example usage (transformers pipeline)
+```py
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+image = Image.open('/content/Thermal-Dogs-and-People-1/test/IMG_0006 5_jpg.rf.cd46e6a862d6ffb7fce6795067ce7cc7.jpg')
+# image = Image.open(requests.get(url, stream=True).raw) # if you want to open from url
+
+obj_detector = pipeline("object-detection", model="faldeus0092/detr-finetuned-thermal-dogs-and-people")
+
+draw = ImageDraw.Draw(image)
+
+for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
+    box = [round(i, 2) for i in box.tolist()]
+    x, y, x2, y2 = tuple(box)
+    draw.rectangle((x, y, x2, y2), outline="red", width=1)
+    draw.text((x, y), model.config.id2label[label.item()], fill="white")
+
+image
+```
+
+