Initial Commit

app.py

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+import cv2
+import gradio as gr
+import math
+import numpy as np
+from cvzone.ClassificationModule import Classifier
+from cvzone.HandTrackingModule import HandDetector
+
+bgSize = 96
+classifier = Classifier("keras_model.h5", "labels.txt")
+detector = HandDetector(maxHands=1)
+labels = ["Look", "Drink", "Eat", "Ok"]
+offset = 20
+
+def segment(image):
+    hands, frame = detector.findHands(image)
+    try:
+        if hands:
+            hand = hands[0]
+            x, y, w, h = hand['bbox']
+            croppedHand = np.ones((bgSize, bgSize, 3), np.uint8) * 12
+            imgCrop = frame[y - offset:y + h +
+                            offset, x - offset:x + w + offset]
+            aspectRatio = h / w
+            if aspectRatio > 1:
+                constant = bgSize / h
+                wComputed = math.floor(constant * w)
+                bgResize = cv2.resize(imgCrop, (wComputed, bgSize))
+                bgResizeShape = bgResize.shape
+                wGap = math.floor((bgSize-wComputed)/2)
+                croppedHand[:bgResizeShape[0],
+                            wGap:wGap + wComputed] = bgResize
+            else:
+                constant = bgSize / w
+                hComputed = math.floor(constant * h)
+                bgResize = cv2.resize(imgCrop, (bgSize, hComputed))
+                bgResizeShape = bgResize.shape
+                hGap = math.floor((bgSize - hComputed) / 2)
+                croppedHand[hGap: hComputed + hGap, :] = bgResize
+            _, index = classifier.getPrediction(croppedHand, draw=False)
+            return labels[index]
+    except Exception as e:
+        print(e)
+    return 'No sign detected'
+
+gr.interface.Interface(fn=segment, live=True, inputs=gr.Image(source='webcam', streaming=True), outputs="text").launch()

keras_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:843e41a49969469d4b5ef0ce6cbb0c35b33467e593f7ed709dc273dbc259e7cd
+size 2453432

labels.txt

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+0 Look
+1 Drink
+2 Eat
+3 Ok

packages.txt

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+python3-opencv

requirements.txt

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+cvzone==1.5.6
+gradio==3.4.1
+numpy==1.23.4
+mediapipe==0.8.11
+opencv_contrib_python==4.6.0.66
+tensorflow==2.10.0