commit e8ce9f226cb041db70c5b92500db50f737a1c13b
Author: Dustin Thomas <stdio@cptlobster.dev>
Date:   Fri Oct 18 18:18:36 2024 -0500

    Initial commit

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..bbe947b
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,15 @@
+### CMake template
+CMakeLists.txt.user
+CMakeCache.txt
+CMakeFiles
+CMakeScripts
+Testing
+Makefile
+cmake_install.cmake
+install_manifest.txt
+compile_commands.json
+CTestTestfile.cmake
+_deps
+CMakeUserPresets.json
+
+.idea
\ No newline at end of file
diff --git a/CMakeLists.txt b/CMakeLists.txt
new file mode 100644
index 0000000..c389abf
--- /dev/null
+++ b/CMakeLists.txt
@@ -0,0 +1,15 @@
+cmake_minimum_required(VERSION 3.29)
+project(pumpkin_tracker)
+
+set(CMAKE_CXX_STANDARD 20)
+
+find_package(OpenCV REQUIRED)
+include_directories(${OpenCV_INCLUDE_DIRS})
+
+FIND_LIBRARY(DarkHelp darkhelp)
+FIND_LIBRARY(Darknet darknet)
+
+ADD_EXECUTABLE(pumpkin_tracker main.cpp)
+TARGET_LINK_LIBRARIES(pumpkin_tracker ${OpenCV_LIBS})
+TARGET_LINK_LIBRARIES(pumpkin_tracker /usr/local/lib/libdarkhelp.so)
+TARGET_LINK_LIBRARIES(pumpkin_tracker /usr/local/lib/libdarknet.so)
\ No newline at end of file
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..40a10ee
--- /dev/null
+++ b/README.md
@@ -0,0 +1,7 @@
+# pumpkin-tracker
+This uses a camera and object detection to estimate the velocity of a flying pumpkin.
+
+## Compiling
+Make sure to compile [Darknet](https://github.com/hank-ai/darknet) (the actual neural network),
+[DarkHelp](https://github.com/stephanecharette/DarkHelp) (a C++ API wrapper for Darknet), and install 
+[OpenCV](https://opencv.com) before compiling this project.
\ No newline at end of file
diff --git a/cfg/coco.names b/cfg/coco.names
new file mode 100644
index 0000000..ca76c80
--- /dev/null
+++ b/cfg/coco.names
@@ -0,0 +1,80 @@
+person
+bicycle
+car
+motorbike
+aeroplane
+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+stop sign
+parking meter
+bench
+bird
+cat
+dog
+horse
+sheep
+cow
+elephant
+bear
+zebra
+giraffe
+backpack
+umbrella
+handbag
+tie
+suitcase
+frisbee
+skis
+snowboard
+sports ball
+kite
+baseball bat
+baseball glove
+skateboard
+surfboard
+tennis racket
+bottle
+wine glass
+cup
+fork
+knife
+spoon
+bowl
+banana
+apple
+sandwich
+orange
+broccoli
+carrot
+hot dog
+pizza
+donut
+cake
+chair
+sofa
+pottedplant
+bed
+diningtable
+toilet
+tvmonitor
+laptop
+mouse
+remote
+keyboard
+cell phone
+microwave
+oven
+toaster
+sink
+refrigerator
+book
+clock
+vase
+scissors
+teddy bear
+hair drier
+toothbrush
diff --git a/cfg/yolov7-tiny.cfg b/cfg/yolov7-tiny.cfg
new file mode 100644
index 0000000..4628b43
--- /dev/null
+++ b/cfg/yolov7-tiny.cfg
@@ -0,0 +1,706 @@
+[net]
+# Testing
+#batch=1
+#subdivisions=1
+# Training
+batch=1
+subdivisions=1
+width=416
+height=416
+channels=3
+momentum=0.9
+decay=0.0005
+angle=0
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.00261
+burn_in=1000
+
+max_batches = 2000200
+policy=steps
+steps=1600000,1800000
+scales=.1,.1
+
+# 0
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=2
+pad=1
+activation=leaky
+
+# 1
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=2
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers=-2
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -5,-3,-2,-1
+
+# 8
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers=-2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -5,-3,-2,-1
+
+# 16
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers=-2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -5,-3,-2,-1
+
+# 24
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[maxpool]
+size=2
+stride=2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers=-2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -5,-3,-2,-1
+
+# 32
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+
+##################################
+
+### SPPCSP ###
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+### SPP ###
+[maxpool]
+stride=1
+size=5
+
+[route]
+layers=-2
+
+[maxpool]
+stride=1
+size=9
+
+[route]
+layers=-4
+
+[maxpool]
+stride=1
+size=13
+
+[route]
+layers=-1,-3,-5,-6
+### End SPP ###
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -10,-1
+
+# 44
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+### End SPPCSP ###
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = 24
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -1,-3
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers=-2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -5,-3,-2,-1
+
+# 56
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = 16
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -1,-3
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers=-2
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -5,-3,-2,-1
+
+# 68
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+##########################
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=2
+pad=1
+filters=128
+activation=leaky
+
+[route]
+layers = -1,56
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers=-2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -5,-3,-2,-1
+
+# 77
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=2
+pad=1
+filters=256
+activation=leaky
+
+[route]
+layers = -1,44
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers=-2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -5,-3,-2,-1
+
+# 86
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+#############################
+
+# ============ End of Neck ============ #
+
+# ============ Head ============ #
+
+
+# P3
+[route]
+layers = 68
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=128
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+#activation=linear
+activation=logistic
+
+[yolo]
+mask = 0,1,2
+anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
+classes=80
+num=9
+jitter=.1
+scale_x_y = 2.0
+objectness_smooth=1
+ignore_thresh = .7
+truth_thresh = 1
+#random=1
+resize=1.5
+iou_thresh=0.2
+iou_normalizer=0.05
+cls_normalizer=0.5
+obj_normalizer=1.0
+iou_loss=ciou
+nms_kind=diounms
+beta_nms=0.6
+new_coords=1
+max_delta=2
+
+
+# P4
+[route]
+layers = 77
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+#activation=linear
+activation=logistic
+
+[yolo]
+mask = 3,4,5
+anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
+classes=80
+num=9
+jitter=.1
+scale_x_y = 2.0
+objectness_smooth=1
+ignore_thresh = .7
+truth_thresh = 1
+#random=1
+resize=1.5
+iou_thresh=0.2
+iou_normalizer=0.05
+cls_normalizer=0.5
+obj_normalizer=1.0
+iou_loss=ciou
+nms_kind=diounms
+beta_nms=0.6
+new_coords=1
+max_delta=2
+
+
+# P5
+[route]
+layers = 86
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+#activation=linear
+activation=logistic
+
+[yolo]
+mask = 6,7,8
+anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
+classes=80
+num=9
+jitter=.1
+scale_x_y = 2.0
+objectness_smooth=1
+ignore_thresh = .7
+truth_thresh = 1
+#random=1
+resize=1.5
+iou_thresh=0.2
+iou_normalizer=0.05
+cls_normalizer=0.5
+obj_normalizer=1.0
+iou_loss=ciou
+nms_kind=diounms
+beta_nms=0.6
+new_coords=1
+max_delta=2
diff --git a/cfg/yolov7-tiny.weights b/cfg/yolov7-tiny.weights
new file mode 100644
index 0000000..c29f934
Binary files /dev/null and b/cfg/yolov7-tiny.weights differ
diff --git a/main.cpp b/main.cpp
new file mode 100644
index 0000000..b2cd927
--- /dev/null
+++ b/main.cpp
@@ -0,0 +1,62 @@
+/* Computer vision demo. Performs object tracking on pumpkins to determine velocity, launch angle, and predicted range.
+ *
+ */
+#include <iostream>
+#include <DarkHelp.hpp>
+#include <unistd.h>
+#include <opencv4/opencv2/core/mat.hpp>
+#include <opencv4/opencv2/videoio.hpp>
+#include <opencv4/opencv2/highgui.hpp>
+
+// Default configuration values. Using YOLOv7 tiny model. Make sure to download the weights.
+#define DARKNET_CFG "cfg/yolov7-tiny.cfg"
+#define DARKNET_WEIGHTS "cfg/yolov7-tiny.weights"
+#define DARKNET_DATA "cfg/coco.names"
+#define CAMERA_ID 0
+#define SHOW_GUI true
+
+using namespace std;
+using namespace cv;
+using namespace DarkHelp;
+
+int main() {
+    // Configure the neural network
+    NN nn(DARKNET_CFG, DARKNET_WEIGHTS, DARKNET_DATA);
+
+    // Setup the capture stream from the webcam
+    VideoCapture cap(CAMERA_ID);
+    if (not cap.isOpened())
+    {
+        throw std::runtime_error("failed to open the webcam");
+    }
+    cap.set(CAP_PROP_FRAME_WIDTH, 640.0);
+    cap.set(CAP_PROP_FRAME_HEIGHT, 480.0);
+    cap.set(CAP_PROP_FPS, 30.0);
+
+    while (cap.isOpened()) {
+        Mat frame;
+
+        cap >> frame;
+        if (frame.empty()) break;
+
+        const PredictionResults results = nn.predict(frame);
+
+        // print results to console
+        cout << "RESULTS" << endl;
+        for (int i = 0; i < results.size(); i++) {
+            const PredictionResult result = results[i];
+            cout << result.name << " | (" << result.original_point.x << ", " << result.original_point.y << ")" << endl;
+        }
+        cout << endl;
+
+        // Sleep between frames; if the UI is enabled, show the latest (annotated) frame
+        if constexpr (SHOW_GUI) {
+            frame = nn.annotate();
+            imshow("pumpkin-tracker", frame);
+            if (const auto key = waitKey(15); key == 27) break;
+        }
+        else {
+            usleep(15000);
+        }
+    }
+}