Add labels files and update readme

DOWNLOAD_WEIGHTS.md

@@ -1,7 +1,7 @@
 ## Instructions to download pretrained neural-network weights.
 
-[GitHub](https://github.com/adipandas/multi-object-tracker)
-[Home](https://adipandas.github.io/multi-object-tracker/)
+[[Webpage](https://adipandas.github.io/multi-object-tracker/)]
+[[GitHub](https://github.com/adipandas/multi-object-tracker)]
 
 ##### YOLOv3
 ```

README.md

@@ -37,31 +37,30 @@ Pip install for OpenCV (version 3.4.3 or later) is available [here](https://pypi
 ```
 git clone https://github.com/adipandas/multi-object-tracker
 cd multi-object-tracker
+pip install -r requirements.txt
 pip install -e .
 ```
 
-Note - for using neural network models with GPU
----
-For using the opencv `dnn`-based object detection modules provided in this repository with GPU, you may have to compile a CUDA enabled version of OpenCV from source.
-
-For building opencv from source, you can refer the following:
+**Note - for using neural network models with GPU**  
+For using the opencv `dnn`-based object detection modules provided in this repository with GPU, you may have to compile a CUDA enabled version of OpenCV from source.  
+* To build opencv from source, refer the following links:
 [[link-1](https://docs.opencv.org/master/df/d65/tutorial_table_of_content_introduction.html)],
 [[link-2](https://www.pyimagesearch.com/2020/02/03/how-to-use-opencvs-dnn-module-with-nvidia-gpus-cuda-and-cudnn/)]
 
 ## How to use?: Examples
 
-Please refer [examples](./examples/) folder of this repository.
-You can clone and run the examples as shown in the [readme](examples/readme.md) inside the [examples](./examples/) folder.
+Please refer [examples](https://github.com/adipandas/multi-object-tracker/tree/master/examples) folder of this repository.
+You can clone and run the examples as shown [here](examples/readme.md).
 
 ## Pretrained object detection models
 
 You will have to download the pretrained weights for the neural-network models. 
-The shell scripts for downloading these are provided in [examples](examples/) folder.  
+The shell scripts for downloading these are provided [here](https://github.com/adipandas/multi-object-tracker/tree/master/examples/pretrained_models) below respective folders.
 Please refer [DOWNLOAD_WEIGHTS.md](DOWNLOAD_WEIGHTS.md) for more details.
 
 ## References and Credits
 
-Please see [REFERENCES.md](REFERENCES.md)
+Please see [REFERENCES.md](REFERENCES.md).
 
 ## Citation
 

examples/pretrained_models/caffemodel_weights/ssd_mobilenet_caffe_names.json

@@ -0,0 +1 @@
+{"0": "background", "1": "aeroplane", "2": "bicycle", "3": "bird", "4": "boat", "5": "bottle", "6": "bus", "7": "car", "8": "cat", "9": "chair", "10": "cow", "11": "diningtable", "12": "dog", "13": "horse", "14": "motorbike", "15": "person", "16": "pottedplant", "17": "sheep", "18": "sofa", "19": "train", "20": "tvmonitor"}

examples/pretrained_models/tensorflow_weights/ssd_mobilenet_v2_coco_names.json

@@ -0,0 +1,11 @@
+{"0": "background", "1": "person", "2": "bicycle", "3": "car", "4": "motorcycle", "5": "airplane", "6": "bus", "7": "train",
+ "8": "truck", "9": "boat", "10": "traffic light", "11": "fire hydrant", "13": "stop sign", "14": "parking meter", "15": "bench",
+ "16": "bird", "17": "cat", "18": "dog", "19": "horse", "20": "sheep", "21": "cow", "22": "elephant", "23": "bear", "24": "zebra",
+ "25": "giraffe", "27": "backpack", "28": "umbrella", "31": "handbag", "32": "tie", "33": "suitcase", "34": "frisbee", "35": "skis",
+ "36": "snowboard", "37": "sports ball", "38": "kite", "39": "baseball bat", "40": "baseball glove", "41": "skateboard", "42": "surfboard",
+ "43": "tennis racket", "44": "bottle", "46": "wine glass", "47": "cup", "48": "fork", "49": "knife", "50": "spoon", "51": "bowl", "52": "banana",
+ "53": "apple", "54": "sandwich", "55": "orange", "56": "broccoli", "57": "carrot", "58": "hot dog", "59": "pizza", "60": "donut", "61": "cake",
+ "62": "chair", "63": "couch", "64": "potted plant", "65": "bed", "67": "dining table", "70": "toilet", "72": "tv", "73": "laptop", "74": "mouse",
+ "75": "remote", "76": "keyboard", "77": "cell phone", "78": "microwave", "79": "oven", "80": "toaster", "81": "sink", "82": "refrigerator",
+ "84": "book", "85": "clock", "86": "vase", "87": "scissors", "88": "teddy bear", "89": "hair drier", "90": "toothbrush"
+}

examples/pretrained_models/yolo_weights/coco_names.json

@@ -0,0 +1,12 @@
+{"0": "person", "1": "bicycle", "2": "car", "3": "motorbike", "4": "aeroplane", "5": "bus", "6": "train", "7": "truck", "8": "boat",
+  "9": "traffic light", "10": "fire hydrant", "11": "stop sign", "12": "parking meter", "13": "bench", "14": "bird", "15": "cat",
+  "16": "dog", "17": "horse", "18": "sheep", "19": "cow", "20": "elephant", "21": "bear", "22": "zebra", "23": "giraffe", "24": "backpack",
+  "25": "umbrella", "26": "handbag", "27": "tie", "28": "suitcase", "29": "frisbee", "30": "skis", "31": "snowboard", "32": "sports ball",
+  "33": "kite", "34": "baseball bat", "35": "baseball glove", "36": "skateboard", "37": "surfboard", "38": "tennis racket", "39": "bottle",
+  "40": "wine glass", "41": "cup", "42": "fork", "43": "knife", "44": "spoon", "45": "bowl", "46": "banana", "47": "apple", "48": "sandwich",
+  "49": "orange", "50": "broccoli",
+  "51": "carrot", "52": "hot dog", "53": "pizza", "54": "donut", "55": "cake", "56": "chair", "57": "sofa",
+  "58": "pottedplant", "59": "bed", "60": "diningtable", "61": "toilet", "62": "tvmonitor", "63": "laptop",
+  "64": "mouse", "65": "remote", "66": "keyboard", "67": "cell phone", "68": "microwave", "69": "oven", "70": "toaster",
+  "71": "sink", "72": "refrigerator", "73": "book", "74": "clock", "75": "vase", "76": "scissors", "77": "teddy bear", "78": "hair drier",
+  "79": "toothbrush"}

examples/readme.md

@@ -1,10 +1,13 @@
 # multi-object-tracker examples
 
-[Home](https://adipandas.github.io/multi-object-tracker/)
-[GitHub](https://github.com/adipandas/multi-object-tracker)
+[[Webpage](https://adipandas.github.io/multi-object-tracker/)]
+[[GitHub](https://github.com/adipandas/multi-object-tracker)]
+
 
 This folder contains various examples.
 
-1. [Example jupyter-notebooks](example_notebooks)
-2. [Example scripts](example_scripts)
-3. [Evaluations based on py-motmetrics](./motmetrics_eval)
+Note: Before using these examples, you will have to download the network models. Please refer [these instructions](../DOWNLOAD_WEIGHTS.md) for downloading.
+
+1. [Example jupyter-notebooks](https://github.com/adipandas/multi-object-tracker/tree/master/examples/example_notebooks)
+2. [Example scripts](https://github.com/adipandas/multi-object-tracker/tree/master/examples/example_scripts)
+3. [Evaluations based on py-motmetrics](https://github.com/adipandas/multi-object-tracker/tree/master/examples/motmetrics_eval)

requirements.txt

@@ -2,7 +2,6 @@ numpy
 scipy
 matplotlib
 pandas
-ipyfilechooser
 opencv-contrib-python
 motmetrics
 setuptools

setup.py

@@ -12,7 +12,6 @@
         'matplotlib',
         'scipy',
         'opencv-contrib-python',
-        'ipyfilechooser',
         'motmetrics'
     ]
 )