updates UI
This commit is contained in:
mike
@@ -799,5 +799,308 @@ class TestAPIRegression(unittest.TestCase):
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except Exception:
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pass
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def test_14_static_serialization_of_deep_metadata(self):
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import edit_api
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import database
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import json
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import os
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from PIL import Image
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# Create dummy image and person record
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fn = "test_deep_meta_serialization_123.png"
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fpath = os.path.join(self.output_dir, fn)
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Image.new("RGB", (10, 10)).save(fpath)
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conn = database.get_db_connection()
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cur = conn.cursor()
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try:
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cur.execute("""
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INSERT INTO person (filename, filepath, group_id, people_count, anatomical_completeness, facial_direction, objects)
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VALUES (%s, %s, %s, %s, %s, %s, %s)
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""", (fn, fpath, "test_group", 2, False, "front", json.dumps([{"tag": "hat", "score": 0.9}])))
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conn.commit()
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finally:
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cur.close()
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database._put_db_connection(conn)
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try:
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# Trigger write static images.json
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edit_api._write_all_static()
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# Read static file and check that the deep metadata properties are serialized correctly
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static_file = os.path.join(self.output_dir, "_data", "images.json")
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self.assertTrue(os.path.exists(static_file))
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with open(static_file, "r") as f:
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data = json.load(f)
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imgs = data.get("images", [])
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matched = [x for x in imgs if x["filename"] == fn]
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self.assertEqual(len(matched), 1)
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item = matched[0]
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# Assert that the serialized dictionary has all of the deep metadata fields
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self.assertEqual(item.get("people_count"), 2)
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self.assertEqual(item.get("anatomical_completeness"), False)
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self.assertEqual(item.get("facial_direction"), "front")
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self.assertEqual(item.get("objects"), [{"tag": "hat", "score": 0.9}])
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finally:
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# Clean up
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if os.path.exists(fpath):
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os.remove(fpath)
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conn = database.get_db_connection()
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cur = conn.cursor()
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try:
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cur.execute("DELETE FROM person WHERE filename = %s", (fn,))
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conn.commit()
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finally:
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cur.close()
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database._put_db_connection(conn)
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# Re-generate static to clean up the dummy entry
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edit_api._write_all_static()
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def test_15_anatomical_completeness_refinement(self):
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import edit_api
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# 17 keypoints matching COCO-17 format: [x, y, score]
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# Nose (0), shoulders (5,6), elbows (7,8), wrists (9,10), hips (11,12), knees (13,14), ankles (15,16)
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# All of them are visible with score >= 0.3, and well within bounds [0.1, 0.9]
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complete_kpts = [
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[50, 10, 0.9], # Nose (0)
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[48, 11, 0.9], # L_Eye (1)
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[52, 11, 0.9], # R_Eye (2)
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[46, 12, 0.9], # L_Ear (3)
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[54, 12, 0.9], # R_Ear (4)
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[40, 20, 0.9], # L_Shoulder (5)
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[60, 20, 0.9], # R_Shoulder (6)
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[35, 35, 0.9], # L_Elbow (7)
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[65, 35, 0.9], # R_Elbow (8)
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[30, 50, 0.9], # L_Wrist (9)
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[70, 50, 0.9], # R_Wrist (10)
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[42, 55, 0.9], # L_Hip (11)
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[58, 55, 0.9], # R_Hip (12)
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[40, 75, 0.9], # L_Knee (13)
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[60, 75, 0.9], # R_Knee (14)
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[40, 90, 0.9], # L_Ankle (15)
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[60, 90, 0.9], # R_Ankle (16)
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]
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# Test complete pose
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res1 = edit_api._detect_anatomical_completeness(complete_kpts, 100, 100)
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self.assertTrue(res1)
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# Test partial pose: missing knees and ankles
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partial_kpts = [list(kp) for kp in complete_kpts]
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for idx in [13, 14, 15, 16]:
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partial_kpts[idx][2] = 0.1 # Hide them
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res2 = edit_api._detect_anatomical_completeness(partial_kpts, 100, 100)
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self.assertFalse(res2)
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# Test cropped pose: ankles too close to bottom edge (y=99 in height=100)
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cropped_bottom_kpts = [list(kp) for kp in complete_kpts]
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cropped_bottom_kpts[15][1] = 99
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cropped_bottom_kpts[16][1] = 99
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res3 = edit_api._detect_anatomical_completeness(cropped_bottom_kpts, 100, 100)
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self.assertFalse(res3)
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def test_16_object_bbox_estimation(self):
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import edit_api
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# Define some realistic keypoints
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kpts = [
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[50, 10, 0.9], # Nose (0)
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[48, 11, 0.9], # L_Eye (1)
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[52, 11, 0.9], # R_Eye (2)
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[46, 12, 0.9], # L_Ear (3)
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[54, 12, 0.9], # R_Ear (4)
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[40, 20, 0.9], # L_Shoulder (5)
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[60, 20, 0.9], # R_Shoulder (6)
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[35, 35, 0.9], # L_Elbow (7)
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[65, 35, 0.9], # R_Elbow (8)
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[30, 50, 0.9], # L_Wrist (9)
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[70, 50, 0.9], # R_Wrist (10)
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[42, 55, 0.9], # L_Hip (11)
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[58, 55, 0.9], # R_Hip (12)
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[40, 75, 0.9], # L_Knee (13)
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[60, 75, 0.9], # R_Knee (14)
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[40, 90, 0.9], # L_Ankle (15)
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[60, 90, 0.9], # R_Ankle (16)
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]
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# Test head / hair tag bbox estimation
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bbox_hair = edit_api._estimate_bbox_for_tag("long_hair", kpts, 100, 100)
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self.assertIsNotNone(bbox_hair)
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self.assertEqual(len(bbox_hair), 4)
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# Bounding box should surround the head/face region, which is y-centered around 10-12.
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# So upper y (bbox_hair[1]) should be relatively small (close to 0/top)
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self.assertLess(bbox_hair[1], 15)
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# Test chest tag bbox estimation
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bbox_breasts = edit_api._estimate_bbox_for_tag("breasts", kpts, 100, 100)
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self.assertIsNotNone(bbox_breasts)
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self.assertEqual(len(bbox_breasts), 4)
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# Should be below shoulders (y=20) and above hips (y=55). Center around 30.
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self.assertGreater(bbox_breasts[1], 15)
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self.assertLess(bbox_breasts[3], 55)
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# Test stomach tag bbox estimation
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bbox_navel = edit_api._estimate_bbox_for_tag("navel", kpts, 100, 100)
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self.assertIsNotNone(bbox_navel)
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self.assertEqual(len(bbox_navel), 4)
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# Should be around the stomach area, i.e. between 35 and 55.
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self.assertGreater(bbox_navel[1], 25)
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# Test arms tag bbox estimation
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bbox_arms = edit_api._estimate_bbox_for_tag("sleeves", kpts, 100, 100)
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self.assertIsNotNone(bbox_arms)
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self.assertEqual(len(bbox_arms), 4)
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# Test legs tag bbox estimation
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bbox_legs = edit_api._estimate_bbox_for_tag("thighs", kpts, 100, 100)
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self.assertIsNotNone(bbox_legs)
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self.assertEqual(len(bbox_legs), 4)
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def test_17_gaze_and_pose_description_enhancements(self):
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import edit_api
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# Test 1: Standard upright front facing pose with direct gaze
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standing_kpts = [
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[50, 12.5, 0.9], # Nose (0)
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[52, 11, 0.9], # L_Eye (1)
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[48, 11, 0.9], # R_Eye (2)
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[54, 12, 0.9], # L_Ear (3)
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[46, 12, 0.9], # R_Ear (4)
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[60, 20, 0.9], # L_Shoulder (5)
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[40, 20, 0.9], # R_Shoulder (6)
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[65, 35, 0.9], # L_Elbow (7)
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[35, 35, 0.9], # R_Elbow (8)
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[70, 50, 0.9], # L_Wrist (9)
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[30, 50, 0.9], # R_Wrist (10)
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[58, 55, 0.9], # L_Hip (11)
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[42, 55, 0.9], # R_Hip (12)
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[60, 75, 0.9], # L_Knee (13)
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[40, 75, 0.9], # R_Knee (14)
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[60, 90, 0.9], # L_Ankle (15)
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[40, 90, 0.9], # R_Ankle (16)
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]
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pose_desc = edit_api._describe_pose(standing_kpts)
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self.assertIn("standing", pose_desc)
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self.assertIn("facing forward", pose_desc)
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gaze = edit_api._detect_facial_direction(standing_kpts)
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self.assertEqual(gaze, "looking forward")
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# Test 2: Gaze look left and up
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left_up_kpts = [list(kp) for kp in standing_kpts]
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# To look left: nose (0) moves to the left (smaller X than ear midpoint 50)
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left_up_kpts[0][0] = 45 # Nose X
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# To look up: nose (0) moves up (y-level close to eye level y=11)
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left_up_kpts[0][1] = 11.2 # Nose Y
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gaze_left_up = edit_api._detect_facial_direction(left_up_kpts)
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self.assertEqual(gaze_left_up, "looking left and up")
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# Test 3: Lying down / reclining pose
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lying_kpts = [list(kp) for kp in standing_kpts]
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# In lying down, nose is at y=10, hips are at y=12 (very horizontal)
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# Head X = 10, Hip X = 80
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lying_kpts[0][0] = 10 # Head X
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lying_kpts[0][1] = 10 # Head Y
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lying_kpts[11][0] = 80 # Hip X
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lying_kpts[11][1] = 12 # Hip Y
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lying_kpts[12][0] = 80
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lying_kpts[12][1] = 12
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pose_desc_lying = edit_api._describe_pose(lying_kpts)
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self.assertIn("lying down", pose_desc_lying)
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def test_18_designer_enhancements(self):
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import unittest.mock as mock
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import edit_api
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# 1. Test Deduplication of Pose Names
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# We will mock the external requests.post LLM call to return some mock poses,
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# one of which collides with an existing pose name in poses.md (e.g., "The Clasp" or "standing")
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mock_raw_response = (
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"# standing\n"
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"This is a standing pose description.\n"
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"Perfect anatomy, photorealistic.\n\n"
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"# Custom Pose\n"
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"This is a custom pose description.\n"
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"Anatomically precise, photorealistic.\n"
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)
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mock_response = mock.Mock()
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mock_response.status_code = 200
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mock_response.json.return_value = {
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"choices": [
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{
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"message": {
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"content": mock_raw_response
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}
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}
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]
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}
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with mock.patch("requests.post", return_value=mock_response) as mock_post:
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# Let's override _load_poses to return {"standing": "existing text"} to force a name collision
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with mock.patch("edit_api._load_poses", return_value={"standing": {"text": "existing text", "beta": False}}):
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payload = {
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"n": 2,
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"context": "standing and custom pose instructions",
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"filename": None,
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"beta": False,
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"messages": None
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}
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response = self.client.post("/designer/generate", json=payload)
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self.assertEqual(response.status_code, 200)
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data = response.json()
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self.assertEqual(data["status"], "success")
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poses = data["poses"]
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# The duplicate "standing" name should be renamed to "standing 2" instead of skipped!
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self.assertIn("standing 2", poses)
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self.assertIn("Custom Pose", poses)
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self.assertEqual(poses["standing 2"], "This is a standing pose description. Perfect anatomy, photorealistic.")
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self.assertEqual(poses["Custom Pose"], "This is a custom pose description. Anatomically precise, photorealistic.")
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# 2. Test Multi-Turn Conversation/History Payload Building
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with mock.patch("requests.post", return_value=mock_response) as mock_post:
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with mock.patch("edit_api._load_poses", return_value={}):
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# Send history messages in the request
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history_messages = [
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{"role": "user", "content": "Initial prompt"},
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{"role": "assistant", "content": "# Some Pose\nbody text"}
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]
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payload_with_history = {
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"n": 1,
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"context": "make them sit down",
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"filename": None,
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"beta": False,
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"messages": history_messages
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}
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response = self.client.post("/designer/generate", json=payload_with_history)
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self.assertEqual(response.status_code, 200)
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# Check that requests.post was called with the correct messages payload
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self.assertTrue(mock_post.called)
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call_args = mock_post.call_args
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called_json = call_args[1]["json"]
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called_messages = called_json["messages"]
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# The payload should contain:
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# 1. System message (DESIGNER_SYSTEM)
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# 2. Initial user prompt
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# 3. Assistant response
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# 4. New user follow-up prompt incorporating "make them sit down"
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self.assertEqual(len(called_messages), 4)
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self.assertEqual(called_messages[0]["role"], "system")
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self.assertEqual(called_messages[1]["role"], "user")
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self.assertEqual(called_messages[1]["content"], "Initial prompt")
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self.assertEqual(called_messages[2]["role"], "assistant")
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self.assertEqual(called_messages[2]["content"], "# Some Pose\nbody text")
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self.assertEqual(called_messages[3]["role"], "user")
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self.assertIn("make them sit down", called_messages[3]["content"])
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if __name__ == "__main__":
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unittest.main()
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