new features

.gitignore

@@ -4,3 +4,8 @@ __pycache__
 /__pycache__
 /__pycache__
 /__pycache__
+/__pycache__
+/test_apple
+/NamedPeople
+/db
+*.pyc

app.py

@@ -5,6 +5,14 @@ import PIL
 from PIL import Image, ImageDraw, ImageFont
 import time
 
+import pandas as pd
+from operator import itemgetter
+import os
+
+def get_named_people():
+	named_people = next(os.walk('db'))[1]
+	return named_people
+
 
 dbackends = [
   ['Haar Cascade (OpenCV)','opencv'], 
@@ -21,57 +29,125 @@ dbackendinfo = 'Detectors with 🌈 require a color image.'
 
 
 with gr.Blocks() as demo:
+	with gr.Tab("Add Named Person"):
 
-	input_image = gr.Image(value="8428_26_SM.jpg")
-	annotated_image = gr.AnnotatedImage()
+		input_image = gr.Image(value="8428_26_SM.jpg")
+		annotated_image = gr.AnnotatedImage()
+		selected_face_info = gr.Textbox(label="Selected Face Info", value="Click on a face above")
+		selected_face_pic = gr.Image(label="Selected Face", value="Click on a face above", height=148)
 
-	#jsontext =  gr.Text(label= "deepface extract_faces results")
-	selected_face_info = gr.Textbox(label="Selected Face Info", value="Click on a face above")
-	selected_face_pic = gr.Image(label="Selected Face", value="Click on a face above")
 
+		def findFaces(imgfile,dbackend):
+			start_time = time.time()
+			print(start_time)
 		
-	
-	def findFaces(imgfile,dbackend):
-		start_time = time.time()
-		print(start_time)
-	
-		face_objs = DeepFace.extract_faces(img_path = imgfile, enforce_detection = False, detector_backend = dbackend)
-
-		numberoffaces = len(face_objs)
-		jsontext = ''
-		global faceannotations
-		faceannotations = []
-		for i, face_obj in enumerate(face_objs,1):
-			face_coordinates = (face_obj["facial_area"]["x"],face_obj["facial_area"]["y"], (face_obj["facial_area"]["x"] + face_obj["facial_area"]["w"]),(face_obj["facial_area"]["y"] + face_obj["facial_area"]["h"]))
-			face_confidence =  "Face " + str(i) + ": "+ "{:.0%}".format(face_obj["confidence"])
-			face_result=[face_coordinates,face_confidence]
-			faceannotations.append(face_result)
-		
-		#jsontext=faceannotations
-		#jsontext=face_objs
-		run_time = str(round((time.time() - start_time),2))
-		results = gr.AnnotatedImage(
-			label= "Detected " + str(numberoffaces) + " faces via " + dbackend + ' in ' + run_time + ' seconds.',
-			value=(imgfile, faceannotations)
+			face_objs = DeepFace.extract_faces(img_path = imgfile, enforce_detection = False, detector_backend = dbackend)
+
+			numberoffaces = len(face_objs)
+			jsontext = ''
+			global faceannotations
+			faceannotations = []
+			for i, face_obj in enumerate(face_objs,1):
+				face_coordinates = (face_obj["facial_area"]["x"],face_obj["facial_area"]["y"], (face_obj["facial_area"]["x"] + face_obj["facial_area"]["w"]),(face_obj["facial_area"]["y"] + face_obj["facial_area"]["h"]))
+				face_confidence =  "Face " + str(i) + ": "+ "{:.0%}".format(face_obj["confidence"])
+				face_result=[face_coordinates,face_confidence]
+				faceannotations.append(face_result)
+			
+			#jsontext=faceannotations
+			#jsontext=face_objs
+			run_time = str(round((time.time() - start_time),2))
+			results = gr.AnnotatedImage(
+				label= "Detected " + str(numberoffaces) + " faces via " + dbackend + ' in ' + run_time + ' seconds.',
+				value=(imgfile, faceannotations)
+			)
+
+			print(run_time)
+			return(results,numberoffaces,run_time)
+
+		dbackendchoice = gr.Radio(choices=dbackends,label='Detector Backend:',info=dbackendinfo,container=True,value='retinaface')
+		gr.Interface(
+			allow_flagging = "never",
+			fn=findFaces,
+			inputs=[input_image, dbackendchoice],
+			outputs=[annotated_image,selected_face_info,selected_face_pic],
 		)
+		
+		def select_section(evt: gr.SelectData):
+			cropped_image = np.array(Image.open(input_image.value['path']))
+			cropped_image = cropped_image[faceannotations[evt.index][0][1]:faceannotations[evt.index][0][3], faceannotations[evt.index][0][0]:faceannotations[evt.index][0][2]]
+			return faceannotations[evt.index], cropped_image
+
+
+		annotated_image.select(select_section, None, [selected_face_info,selected_face_pic])
+
+	with gr.Tab("Find Named Person in All Images"):
+		with gr.Row():
+			
+			named_people_dropdown = []
+			for named_person in get_named_people():
+				named_people_dropdown.append(named_person.replace("_"," "))
+			find_list = gr.Dropdown(named_people_dropdown, label="Person", info="Select a Named Person."),
+			find_button = gr.Button(value="Find this person")
+
 
-		print(run_time)
-		return(results,numberoffaces,run_time,)
+	with gr.Tab("Identify People in One Image"):
+		oneimageannotations = []
+		def identify_in_one_image(imgfile):
+			oneimageresults = DeepFace.find(img_path=imgfile, db_path="db")
+			oneimageresults = pd.concat(oneimageresults)
+			for i, found_face in oneimageresults.iterrows():
+				face_coordinates = (found_face["source_x"],found_face["source_y"], (found_face["source_x"] + found_face["source_w"]),(found_face["source_y"] + found_face["source_h"]))
+				person = found_face["identity"].split("/")[1].replace("_"," ")
+				face_confidence = "Matched " + person + " {:.0%}".format(found_face["distance"])
+				face_result=[face_coordinates,face_confidence]
+				oneimageannotations.append(face_result)
+			
+			results = gr.AnnotatedImage(
+				value=(imgfile, oneimageannotations)
+			)
+			return results, oneimageannotations
 
-	dbackendchoice = gr.Radio(choices=dbackends,label='Detector Backend:',info=dbackendinfo,container=True,value='retinaface')
-	gr.Interface(
-		allow_flagging = "never",
-		fn=findFaces,
-		inputs=[input_image, dbackendchoice],
-		outputs=[annotated_image,selected_face_info,selected_face_pic],
-	)
-	def select_section(evt: gr.SelectData):
-		cropped_image = np.array(Image.open(input_image.value['path']))
-		cropped_image = cropped_image[faceannotations[evt.index][0][1]:faceannotations[evt.index][0][3], faceannotations[evt.index][0][0]:faceannotations[evt.index][0][2]]
-		return faceannotations[evt.index], cropped_image
+		oneimage_input_image = gr.Image()
+		
+		found_faces=gr.AnnotatedImage()
+		debug_output = gr.Textbox()
+		gr.Interface(
+			allow_flagging = "never",
+			fn=identify_in_one_image,
+			inputs=oneimage_input_image,
+			outputs=[found_faces, debug_output]
+			)
+		
+			
+
+
+
+	with gr.Tab("Modify Named Person") as ModifyNamedPersonTab:
+
+		
+		def get_named_people_dropdown():
+			named_people_gallery_imgs = []
+			named_people_gallery_captions = []
+			for named_person in get_named_people():
+					#named_person = named_person.replace("_"," ")
+					named_people_gallery_imgs.append("NamedPeople/" + named_person.replace("_","") + ".jpg")
+					named_people_gallery_captions.append(named_person.replace("_"," "))
+					named_people_gallery_all = list(zip(named_people_gallery_imgs, named_people_gallery_captions))
+			images = named_people_gallery_all
 
+			images.sort(key=itemgetter(1))
+			return images
 
-	annotated_image.select(select_section, None, [selected_face_info,selected_face_pic])
+		named_person_gallery = gr.Gallery(
+        label="Named People", elem_id="gallery", object_fit="none", columns=9)
+
+		ModifyNamedPersonTab.select(get_named_people_dropdown, None, named_person_gallery)
+
+	#jsontext =  gr.Text(label= "deepface extract_faces results")
+
+
+
+	
 
 demo.launch(show_error=True)