From 23d94e4846bf4ec13069703a28b1d776f4bbe44f Mon Sep 17 00:00:00 2001
From: Edmond Yoo <hj3yoo@uwaterloo.ca>
Date: Sat, 13 Oct 2018 18:49:47 +0000
Subject: [PATCH] Cleaning & commenting #3 - refactoring constants to Config class

---
 darknet.py |  116 +++++++++++++++++++++++++++++++++++++++++++++++++++++-----
 1 files changed, 106 insertions(+), 10 deletions(-)

diff --git a/darknet.py b/darknet.py
index 2deff4f..f00356d 100644
--- a/darknet.py
+++ b/darknet.py
@@ -31,6 +31,8 @@
 import math
 import random
 import os
+import cv2
+import numpy as np
 
 def sample(probs):
     s = sum(probs)
@@ -78,13 +80,14 @@
 #lib = CDLL("darknet.so", RTLD_GLOBAL)
 hasGPU = True
 if os.name == "nt":
-    winGPUdll = "yolo_cpp_dll.dll"
-    winNoGPUdll = "yolo_cpp_dll_nogpu.dll"
+    cwd = os.path.dirname(__file__)
+    os.environ['PATH'] = cwd + ';' + os.environ['PATH']
+    winGPUdll = os.path.join(cwd, "yolo_cpp_dll.dll")
+    winNoGPUdll = os.path.join(cwd, "yolo_cpp_dll_nogpu.dll")
     envKeys = list()
     for k, v in os.environ.items():
         envKeys.append(k)
     try:
-        tmp = os.environ["CUDA_HOME"]
         try:
             tmp = os.environ["FORCE_CPU"].lower()
             if tmp in ["1", "true", "yes", "on"]:
@@ -118,7 +121,7 @@
             lib = CDLL(winGPUdll, RTLD_GLOBAL)
             print("Environment variables indicated a CPU run, but we didn't find `"+winNoGPUdll+"`. Trying a GPU run anyway.")
 else:
-    lib = CDLL("./libdarknet.so", RTLD_GLOBAL)
+    lib = CDLL("./darknet.so", RTLD_GLOBAL)
 lib.network_width.argtypes = [c_void_p]
 lib.network_width.restype = c_int
 lib.network_height.argtypes = [c_void_p]
@@ -221,10 +224,17 @@
     Performs the meat of the detection
     """
     #pylint: disable= C0321
-    im = load_image(image, 0, 0)
+    if isinstance(image, np.ndarray):
+        im = array_to_image(image)[0]
+    else:
+        im = load_image(image, 0, 0)
+    #import cv2
+    #custom_image_bgr = cv2.imread(image) # use: detect(,,imagePath,)
+    #custom_image = cv2.cvtColor(custom_image_bgr, cv2.COLOR_BGR2RGB)
+    #custom_image = cv2.resize(custom_image,(lib.network_width(net), lib.network_height(net)), interpolation = cv2.INTER_LINEAR)
     #import scipy.misc
-    #sci_image = scipy.misc.imread(image)
-    #im, arr = array_to_image(sci_image)		# you should comment line below: free_image(im)
+    #custom_image = scipy.misc.imread(image)
+    #im, arr = array_to_image(custom_image)		# you should comment line below: free_image(im)
     if debug: print("Loaded image")
     num = c_int(0)
     if debug: print("Assigned num")
@@ -232,7 +242,8 @@
     if debug: print("Assigned pnum")
     predict_image(net, im)
     if debug: print("did prediction")
-    dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, None, 0, pnum, 1)
+    #dets = get_network_boxes(net, custom_image_bgr.shape[1], custom_image_bgr.shape[0], thresh, hier_thresh, None, 0, pnum, 0) # OpenCV
+    dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, None, 0, pnum, 0)
     if debug: print("Got dets")
     num = pnum[0]
     if debug: print("got zeroth index of pnum")
@@ -359,7 +370,9 @@
     if not os.path.exists(imagePath):
         raise ValueError("Invalid image path `"+os.path.abspath(imagePath)+"`")
     # Do the detection
-    detections = detect(netMain, metaMain, imagePath.encode("ascii"), thresh)
+    #detections = detect(netMain, metaMain, imagePath, thresh)	# if is used cv2.imread(image)
+    #detections = detect(netMain, metaMain, imagePath.encode("ascii"), thresh)
+    detections = detect(netMain, metaMain, cv2.imread(imagePath), thresh, debug=True)
     if showImage:
         try:
             from skimage import io, draw
@@ -414,5 +427,88 @@
             print("Unable to show image: "+str(e))
     return detections
 
+
+def capture(thresh=.25, hier_thresh=.5, nms=.45, configPath="./cfg/yolov3.cfg", weightPath="yolov3.weights",
+            metaPath="./data/coco.data", showImage=True, makeImageOnly=False, initOnly=False):
+    global metaMain, netMain, altNames  # pylint: disable=W0603
+    netMain = load_net_custom(configPath.encode("ascii"), weightPath.encode("ascii"), 0, 1)  # batch size = 1
+    metaMain = load_meta(metaPath.encode("ascii"))
+
+    num = c_int(0)
+    pnum = pointer(num)
+    num = pnum[0]
+
+    capture = cv2.VideoCapture('../data/test1.mp4')
+    print(capture.get(cv2.CAP_PROP_FPS))
+
+    capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1024)
+    capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 768)
+
+    while True:
+        ret, frame = capture.read()
+        detections = detect(netMain, metaMain, frame, thresh, debug=True)
+        '''
+        im, arr = array_to_image(frame)
+        predict_image(netMain, im)
+        dets = get_network_boxes(netMain, im.w, im.h, thresh, hier_thresh, None, 0, pnum, 1)
+        if nms:
+            do_nms_sort(dets, num, metaMain.classes, nms)
+        res = []
+        for j in range(num):
+            for i in range(metaMain.classes):
+                if dets[j].prob[i] > 0:
+                    b = dets[j].bbox
+                    nameTag = metaMain.names[i]
+                    res.append((nameTag, dets[j].prob[i], (b.x, b.y, b.w, b.h)))
+        '''
+        for detection in detections:
+            label = detection[0]
+            confidence = detection[1]
+            pstring = label + ": " + str(np.rint(100 * confidence)) + "%"
+            imcaption.append(pstring)
+            print(pstring)
+            bounds = detection[2]
+            shape = image.shape
+            # x = shape[1]
+            # xExtent = int(x * bounds[2] / 100)
+            # y = shape[0]
+            # yExtent = int(y * bounds[3] / 100)
+            yExtent = int(bounds[3])
+            xEntent = int(bounds[2])
+            # Coordinates are around the center
+            xCoord = int(bounds[0] - bounds[2] / 2)
+            yCoord = int(bounds[1] - bounds[3] / 2)
+            boundingBox = [
+                [xCoord, yCoord],
+                [xCoord, yCoord + yExtent],
+                [xCoord + xEntent, yCoord + yExtent],
+                [xCoord + xEntent, yCoord]
+            ]
+            # Wiggle it around to make a 3px border
+            rr, cc = draw.polygon_perimeter([x[1] for x in boundingBox], [x[0] for x in boundingBox], shape=shape)
+            rr2, cc2 = draw.polygon_perimeter([x[1] + 1 for x in boundingBox], [x[0] for x in boundingBox], shape=shape)
+            rr3, cc3 = draw.polygon_perimeter([x[1] - 1 for x in boundingBox], [x[0] for x in boundingBox], shape=shape)
+            rr4, cc4 = draw.polygon_perimeter([x[1] for x in boundingBox], [x[0] + 1 for x in boundingBox], shape=shape)
+            rr5, cc5 = draw.polygon_perimeter([x[1] for x in boundingBox], [x[0] - 1 for x in boundingBox], shape=shape)
+            boxColor = (int(255 * (1 - (confidence ** 2))), int(255 * (confidence ** 2)), 0)
+            draw.set_color(image, (rr, cc), boxColor, alpha=0.8)
+            draw.set_color(image, (rr2, cc2), boxColor, alpha=0.8)
+            draw.set_color(image, (rr3, cc3), boxColor, alpha=0.8)
+            draw.set_color(image, (rr4, cc4), boxColor, alpha=0.8)
+            draw.set_color(image, (rr5, cc5), boxColor, alpha=0.8)
+        print(res)
+        cv2.imshow('frame', frame)
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    capture.release()
+    cv2.destroyAllWindows()
+
+
 if __name__ == "__main__":
-    print(performDetect())
+    performDetect(imagePath='data/scream.jpg')
+    #performDetect(imagePath="../data/test1.jpg", thresh=0.25, configPath="./cfg/tiny_yolo.cfg",
+    #              weightPath="./weights/second_general/tiny_yolo_17000.weights",
+    #              metaPath="./data/obj.data", showImage=True, makeImageOnly=False, initOnly=False)
+    #print(performDetect(showImage=False))
+    #capture()

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