From 0f185fc51ef0c32596af6a492b2ba47ff574787b Mon Sep 17 00:00:00 2001
From: Preethi Satish <pr2satish@gmail.com>
Date: Fri, 21 Jun 2024 00:10:48 -0700
Subject: [PATCH] made threshold vals more clear
---
.../__pycache__/detector.cpython-38.pyc | Bin 2047 -> 2245 bytes
src/main/python/detector.py | 12 ++++--------
src/main/python/test.py | 5 ++++-
3 files changed, 8 insertions(+), 9 deletions(-)
diff --git a/src/main/python/__pycache__/detector.cpython-38.pyc b/src/main/python/__pycache__/detector.cpython-38.pyc
index 802fe1f19955dbc7531ff255f48143741c7c89f2..66288f96cbf7123d617ac11f619a3d00ec23daa1 100644
GIT binary patch
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diff --git a/src/main/python/detector.py b/src/main/python/detector.py
index 4115374..caedfd9 100644
--- a/src/main/python/detector.py
+++ b/src/main/python/detector.py
@@ -7,12 +7,8 @@
# define orange hsv values (opencv range is h:0-180, s:0-255, v:0-255)
# NOTE: BELOW VALS REPRESENT RED ACTUALLY BC I ONLY HAD A RED SPONGE TO USE
-LOWER_ORANGE_HSV = np.array([3, 80, 80])
-UPPER_ORANGE_HSV = np.array([6, 255, 255])
-
-LOW_THRESHOLD = 110
-HIGH_THRESHOLD = 255
-
+# LOWER_ORANGE_HSV = np.array([3, 80, 80])
+# UPPER_ORANGE_HSV = np.array([6, 255, 255])
# orange hsv values
# LOWER_ORANGE_HSV = np.array([3, 80, 80])
@@ -28,11 +24,11 @@ class Detector:
def __init__(self):
pass
- def detectOrange(self, grayscale_image, threshold):
+ def detectOrange(self, grayscale_image, low_threshold, high_threshold):
"""NOTE: to threshold with monochrome image (single-channel, grayscale) to create a binary mask,
can specify a SINGLE scalar value for lower/upper bounds
returns: binary image (single-channel, 8-bit)"""
- return cv2.inRange(grayscale_image, LOW_THRESHOLD, HIGH_THRESHOLD)
+ return cv2.inRange(grayscale_image, low_threshold, high_threshold)
#return np.where(grayscale_image > threshold, 255, 0).astype(np.uint8)
def find_largest_orange_contour(self, orange_mask: np.ndarray) -> np.ndarray:
diff --git a/src/main/python/test.py b/src/main/python/test.py
index 320ee2f..1404813 100644
--- a/src/main/python/test.py
+++ b/src/main/python/test.py
@@ -7,6 +7,9 @@
cap = cv2.VideoCapture(0)
counter = 0
+LOW_THRESHOLD = 110
+HIGH_THRESHOLD = 255
+
while(True):
ret, frame = cap.read()
@@ -24,7 +27,7 @@
# convert tuple from (height, width, # of channels) to just (height, width)
frame_single_channel = frame[:,:,0]
- orange_mask = d.detectOrange(frame_single_channel, threshold=100)
+ orange_mask = d.detectOrange(frame_single_channel, LOW_THRESHOLD, HIGH_THRESHOLD)
contour = d.find_largest_orange_contour(orange_mask)
#cv2.drawContours(frame, contour, 0, [255, 0, 0], 2)
if contour is not None and d.contour_is_note(contour):