camera feed

Author: Arash Hosseini

demo_camera.py

@@ -1 +1,47 @@
-# TODO
+import demo_image 
+import argparse
+import cv2
+import time
+import config
+from model import get_testing_model
+import json
+import os
+
+if __name__ == '__main__':
+	parser = argparse.ArgumentParser()
+	parser.add_argument('--output', type=str, default='result.png', help='output image')
+	parser.add_argument('--model', type=str, default='model/keras/model.h5', help='path to the weights file')
+	args = parser.parse_args()
+	output = args.output
+	keras_weights_file = args.model
+
+	tic = time.time()
+	print('start processing...')
+	# load model
+	# authors of original model don't use
+	# vgg normalization (subtracting mean) on input images
+	model = get_testing_model(38,19)
+	model.load_weights(keras_weights_file)
+	# load config
+	_config = config.GetConfig("Canonical")
+	toc = time.time()
+	print ('processing time is %.5f' % (toc - tic))
+	cam = cv2.VideoCapture(0)
+	frame = 0
+	while True:
+		ret_val, canvas = cam.read()
+		if ret_val:
+			scanvas, pose_keypoints = demo_image.process(canvas,
+														_config,
+														model)
+
+		with open(os.path.join("./json", '{0}_keypoints.json'.format(str(frame).zfill(12))), 'w') as outfile:
+			 json.dump(pose_keypoints, outfile)
+
+		cv2.imshow('keras Pose Estimation', canvas)
+		cv2.imwrite(output, canvas)
+		frame += 1
+		if cv2.waitKey(1) == 27:
+			break
+
+	cv2.destroyAllWindows()

demo_image.py

@@ -27,9 +27,14 @@
           [170, 0, 255], [255, 0, 255], [255, 0, 170], [255, 0, 85]]
 
 
-def process (input_image, params):
-    oriImg = cv2.imread(input_image)  # B,G,R order
-    print (oriImg.shape[0], params.width)
+
+
+def process (input_image, params, model):
+
+    oriImg = input_image
+    if isinstance(input_image, str):
+        oriImg = cv2.imread(input_image)  # B,G,R order
+
     multiplier = [x * params.width / oriImg.shape[0] for x in params.scale_search]
 
     heatmap_avg = np.zeros((oriImg.shape[0], oriImg.shape[1], 19))
@@ -201,11 +206,9 @@ def process (input_image, params):
     subset = np.delete(subset, deleteIdx, axis=0)
     flat = [0.0 for i in range(36)]
     dc = {"people":[]}
-    canvas = cv2.imread(input_image)  # B,G,R order
+    canvas = oriImg  # B,G,R order
     for i in range(18):
         for j in range(len(all_peaks[i])):
-            print (all_peaks[i][j][0:2])
-
             flat[i*2] = int(all_peaks[i][j][0:2][0])
             flat[i*2+1] = int(all_peaks[i][j][0:2][1])
             cv2.circle(canvas, all_peaks[i][j][0:2], 4, colors[i], thickness=-1)
@@ -248,12 +251,12 @@ def process (input_image, params):
     # load model
     # authors of original model don't use
     # vgg normalization (subtracting mean) on input images
+
     model = get_testing_model(38,19)
     model.load_weights(keras_weights_file)
-
     # load config
     _config = config.GetConfig("Canonical")
-    canvas, pose_keypoints = process(input_image, _config)
+    canvas, pose_keypoints = process(input_image, _config, model)
 
     toc = time.time()
     print ('processing time is %.5f' % (toc - tic))